Cobinatorial Algorithms for Nearest Neighbors, Near-Duplicates and Small World Design - Yury Lifshits - SODA 2009
0 likes787 views
This document presents research on combinatorial algorithms for nearest neighbor search, near-duplicate detection, and small-world network design. It introduces a combinatorial framework based on a comparison oracle and disorder inequality that does not require triangle inequality. This framework is used to develop new exact algorithms for nearest neighbor search and near-duplicate detection that run in polynomial time in the disorder parameter. It also shows how to construct a visibility graph for any dataset in polynomial time that allows greedy routing to find the nearest neighbor in logarithmic hops.
1 of 45
Downloaded 32 times
Recommended
Number Crunching in Python
Number Crunching in PythonValerio Maggio
油
"Number Crunching in Python": slides presented at EuroPython 2012, Florence, Italy
際際滷s have been authored by me and by Dr. Enrico Franchi.
Scientific and Engineering Computing, Numpy NDArray implementation and some working case studies are reported.Metody logiczne w analizie danych 
Metody logiczne w analizie danych Data Science Warsaw
油
This document presents an overview of the Tolerance Rough Set Model (TRSM) and its applications in web intelligence and document clustering. The TRSM uses a tolerance relation instead of an indiscernibility relation to define rough set approximations. This model is used for clustering web search results by enriching document representations with terms from tolerance classes and then applying k-means clustering. An extended TRSM incorporates a thesaurus to further expand document representations. The document concludes by describing SONCA, a search platform that applies these rough set methods along with semantic indexing to perform advanced querying over document collections.Calculating Projections via Type Checking
Calculating Projections via Type CheckingDaisuke BEKKI
油
Bekki Daisuke and Miho Sato (2015).
A presentation in TYpe Theory and LExical Semantics (TYTLES) in the 27th European Summer School in Logic, Language and Information (ESSLLI 2015), Barcelona, Spain.Algorithms and Complexity: Cryptography Theory
Algorithms and Complexity: Cryptography TheoryAlex Prut
油
This document discusses algorithms and complexity in cryptography. It begins by defining function problems in computational complexity theory as computational problems where the expected output is more complex than a simple yes or no answer. It then discusses one-way functions, which are easy to compute but believed to be hard to invert. The document provides examples of one-way functions based on integer multiplication, discrete logarithms, and the RSA cryptosystem. It argues that the existence of one-way functions separates the complexity classes P and UP, and that cryptography relies on the assumption that stronger versions of one-way functions exist."That scripting language called Prolog"
"That scripting language called Prolog"Sergei Winitzki
油
What is "logic programming" and "constraint programming"
Prolog in a nutshell
How Prolog "makes pointers safe"
Why Prolog was the ultimate scripting language for AI (backtracking search, interpreters, and DSLs for free)
What is "functional-logic programming" (a taste of the programming language Mercury)
Video recording of the talk: http://youtu.be/Fhc7fPQF1iY足Master Thesis on the Mathematial Analysis of Neural Networks
Master Thesis on the Mathematial Analysis of Neural NetworksAlina Leidinger
油
Master Thesis submitted on June 15, 2019 at TUM's chair of Applied Numerical Analysis (M15) at the Mathematics Department.The project was supervised by Prof. Dr. Massimo Fornasier. The thesis took a detailed look at the existing mathematical analysis of neural networks focusing on 3 key aspects: Modern and classical results in approximation theory, robustness and Scattering Networks introduced by Mallat, as well as unique identification of neural network weights. See also the one page summary available on 際際滷share.slides_low_rank_matrix_optim_farhad
slides_low_rank_matrix_optim_farhadFarhad Gholami
油
The document discusses low-rank matrix optimization problems and heuristics for solving rank minimization problems. It covers the following key points in 3 sentences:
The document outlines motivation for extracting low-dimensional structures from high-dimensional data using rank minimization. It then discusses several heuristics for approximating the non-convex rank minimization problem, including replacing the rank with the nuclear norm, using the log-det heuristic as a smooth surrogate, matrix factorization methods, and iteratively solving a sequence of rank-constrained convex problems. Applications mentioned include the Netflix Prize and video intrusion detection.M16302
M16302josefamontano
油
This document defines statistical symbols and their meanings that are used throughout a statistics textbook. It provides the symbol, how it is spoken, and a brief definition of its meaning. Some key symbols defined include population mean (亮), sample mean (x), standard deviation (s), probability (P), normal distribution (N), z-score, confidence level, confidence interval, null hypothesis (H0), and alternate hypothesis (H1). The document is organized by statistical topic and lists over 50 common statistical symbols.Simulation Informatics; Analyzing Large Scientific Datasets
Simulation Informatics; Analyzing Large Scientific DatasetsDavid Gleich
油
1) The document discusses using large datasets from scientific simulations to analyze uncertainty quantification (UQ) through techniques like randomized parameter studies and reduced order modeling.
2) The author presents work using PageRank as a test case for examining UQ and developing generalized methods for studying parameterized matrix equations.
3) The approach involves constructing an interpolating reduced order model from an ensemble of pre-computed simulation runs stored in a data cluster to enable engineers to efficiently query simulation data for statistical analysis and UQ studies without running new expensive simulations.Drugs and Electrons
Drugs and ElectronsDavid Thompson
油
The document discusses the author's work using computational chemistry methods to develop new drugs through structure-based drug design, explores information theoretic properties of confined electronic systems, and proposes a novel 3D quantum mechanics-based structural descriptor called Sr that could be used for molecular similarity comparisons based on approximating the electron density distribution.Nelly Litvak Asymptotic behaviour of ranking algorithms in directed random ...
Nelly Litvak Asymptotic behaviour of ranking algorithms in directed random ...Yandex
油
There is a vast empirical research on the behaviour of ranking algorithms, e.g. Google PageRank, in scale-free networks. In this talk, we address this problem by analytical probabilistic methods. In particular, it is well-known that the PageRank in scale-free networks follows a power law with the same exponent as in-degree. Recent probabilistic analysis has provided an explanation for this phenomenon by obtaining a natural approximation for PageRank based on stochastic fixed-point equations. For these equations, explicit solutions can be constructed on weighted branching trees, and their tail behavior can be described in great detail.
In this talk we present a model for generating directed random graphs with prescribed degree distributions where we can prove that the PageRank of a randomly chosen node does indeed converge to the solution of the corresponding fixed-point equation as the number of nodes in the graph grows to infinity. The proof of this result is based on classical random graph coupling techniques combined with the now extensive literature on the behavior of branching recursions on trees.Class 11: Deeper List Procedures
Class 11: Deeper List ProceduresDavid Evans
油
list-accumulate vs. list-cruncher
The Story so Far: Recursive Definitions, Universality, Abstraction
Problem Set 3: L-System FractalsPertemuan 5_Relation Matriks_01 (17)
Pertemuan 5_Relation Matriks_01 (17)Evert Sandye Taasiringan
油
The document discusses relations and their application to databases in the relational data model. It defines binary and n-ary relations, and explains how databases can be represented as n-ary relations with records as n-tuples consisting of fields. Primary keys are introduced as fields that uniquely identify each record. Common relational operations like projection and join are explained, with examples provided to illustrate how they transform relations.Computing Local and Global Centrality
Computing Local and Global CentralityDavid Gleich
油
Some recent results on computing PageRank and Katz scores on large networks that I presented at a Dagstuhl workshop.A Primer on Entity Resolution
A Primer on Entity ResolutionBenjamin Bengfort
油
Entity Resolution is the task of disambiguating manifestations of real world entities through linking and grouping and is often an essential part of the data wrangling process. There are three primary tasks involved in entity resolution: deduplication, record linkage, and canonicalization; each of which serve to improve data quality by reducing irrelevant or repeated data, joining information from disparate records, and providing a single source of information to perform analytics upon. However, due to data quality issues (misspellings or incorrect data), schema variations in different sources, or simply different representations, entity resolution is not a straightforward process and most ER techniques utilize machine learning and other stochastic approaches.Prolog Cpt114 - Week 2
Prolog Cpt114 - Week 2a_akhavan
油
This document discusses Prolog and provides examples of:
- Defining facts and rules to represent relationships like parent/child
- Using recursion to define indirect relationships like being a predecessor to someone
- Using path/2 to recursively find all paths between two nodes through arcs
It gives examples of queries to find paths between nodes in a graph.Fast matrix primitives for ranking, link-prediction and more
Fast matrix primitives for ranking, link-prediction and moreDavid Gleich
油
This document summarizes a presentation about fast matrix computations and their applications. It discusses using matrix methods to solve problems related to recommendation systems, network analysis, and ranking aggregation more efficiently. Specific algorithms discussed include PageRank, heat kernels, and nuclear norm ranking. It also describes theoretical guarantees for localization and runtime of these algorithms, as well as empirical evaluations demonstrating their accuracy and performance on real-world datasets.Introduction to Probabilistic Latent Semantic Analysis
Introduction to Probabilistic Latent Semantic AnalysisNYC Predictive Analytics
油
The document provides an introduction to Probabilistic Latent Semantic Analysis (PLSA). It discusses how PLSA improves on previous Latent Semantic Analysis methods by incorporating a probabilistic framework. PLSA models documents as mixtures of topics and allows words to have multiple meanings. The parameters of the PLSA model, including the topic distributions and word-topic distributions, are estimated using an expectation-maximization algorithm to find the parameters that best explain the observed word-document co-occurrence data.CVPR2010: higher order models in computer vision: Part 1, 2
CVPR2010: higher order models in computer vision: Part 1, 2zukun
油
This document discusses tractable higher order models in computer vision using random field models. It introduces Markov random fields (MRFs) and factor graphs as graphical models for computer vision problems. Higher order models that include factors over cliques of more than two variables can model problems more accurately but are generally intractable. The document discusses various inference techniques for higher order models such as relaxation, message passing, and decomposition methods. It provides examples of how higher order and global models can be used in problems like segmentation, stereo matching, reconstruction, and denoising.際際滷s4
際際滷s4BioinformaticsInstitute
油
GraphClust is an alignment-free method for clustering RNA sequences based on their secondary structures. It represents RNA secondary structures as labeled graphs and uses a graph kernel called NSPDK to compute similarities between graphs. GraphClust clusters RNAs in a linear time complexity by using MinHash to identify candidate neighborhoods for clustering, then refines clusters with sequence-structure alignment tools. It was able to cluster hundreds of thousands of RNA sequences in under a month, while traditional alignment-based methods would take hundreds of computer years for the same task.Anti-differentiating Approximation Algorithms: PageRank and MinCut
Anti-differentiating Approximation Algorithms: PageRank and MinCutDavid Gleich
油
We study how Google's PageRank method relates to mincut and a particular type of electrical flow in a network. We also explain the details of how the "push method" for computing PageRank helps to accelerate it. This has implications for semi-supervised learning and machine learning, as well as social network analysis.Spectral graph theory
Spectral graph theoryDanushka Bollegala
油
Spectral clustering works by creating an affinity matrix from a similarity matrix and then applying dimensionality reduction before clustering in the reduced space. It represents the data as an undirected graph and uses the graph Laplacian matrix to perform the dimensionality reduction. The number of clusters can be determined using the eigengap heuristic or by setting k equal to the logarithm of the number of data points. The Gaussian kernel is commonly used to create the affinity matrix from the similarity matrix.[ICDE 2012] On Top-k Structural Similarity Search![[ICDE 2012] On Top-k Structural Similarity Search](https://cdn.slidesharecdn.com/ss_thumbnails/topsim-v3-140416141822-phpapp01-thumbnail.jpg?width=560&fit=bounds)
[ICDE 2012] On Top-k Structural Similarity SearchPei Lee
油
In this talk, we talk about the following classic problem: given a node in a graph, how can we efficiently track the top-k similar nodes regarding this node, by simply checking the graph link structure? This talk is accompanying with the ICDE 2012 paper "On Top-k Structural Similarity Search", which can be found at http://www.cs.ubc.ca/~peil/research.htmlSimilarity Search in High Dimensions via Hashing
Similarity Search in High Dimensions via HashingMaruf Aytekin
油
This document discusses locality-sensitive hashing (LSH) for similarity search in high dimensions. It introduces LSH as a technique to "hash" similar items to the same bucket with high probability. Locality-sensitive functions are defined that map similar items to the same value more often than dissimilar items. The banding technique divides the data into bands to improve performance. LSH families are described for cosine similarity. Applications include near neighbor search, entity resolution, and matching fingerprints or articles.MUMS Opening Workshop - Emulators for models and Complexity Reduction - Akil ...
MUMS Opening Workshop - Emulators for models and Complexity Reduction - Akil ...The Statistical and Applied Mathematical Sciences Institute
油
The document discusses emulators, which are used to approximate complex models. Emulators take the form of a linear combination of basis functions fitted to available data. Two types of emulators are discussed: linear approximations, where the basis functions are fixed beforehand, and nonlinear approximations, where the basis functions depend on the data. Experimental design for collecting data is critical for building an accurate emulator.pres_coconat
pres_coconatGabriel Gaudreault
油
Gabriel Gaudreault presents a functional calculus called 了-calculus for doing semantics with pregroup grammars. The calculus allows functional composition as the main reduction operation and respects the incoming direction of inputs. There is a 1-1 correspondence between the calculus and a subset of pregroup grammars relevant for linguistic analysis. The calculus can be used for syntactic and semantic analysis of natural language examples. Future work includes further analysis of the semantic power of the calculus and proving properties like Church-Rosser.Chapter 10 link prediction
Chapter 10 link predictionAbanobZakaria1
油
This document discusses link prediction using graph neural networks. It begins with an introduction to link prediction and traditional methods like heuristics and latent feature models. It then discusses how graph neural networks can be used for link prediction, including node-based methods like graph autoencoders that learn node embeddings, and subgraph-based methods that extract local neighborhoods. The document outlines some popular graph neural network models for link prediction and areas for future work.Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks 
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks Christopher Morris
油
This document proposes methods to incorporate higher-order graph properties into graph neural networks (GNNs). It shows that GNNs are as powerful as the 1-dimensional Weisfeiler-Lehman graph isomorphism test for distinguishing graphs, but cannot capture higher-order properties like triangle counts. The document introduces k-dimensional GNNs and hierarchical k-GNNs to learn representations of subgraphs. Experimental results show these methods improve over 1-GNN baselines on graph classification and regression tasks.Osh Curiosity Learning on Mobile
Osh Curiosity Learning on MobileYury Lifshits
油
The document describes different types of learning units available in the Osh learning app, including:
1. Streams which allow users to choose topics and scroll through cards with images, short texts, and facts to learn.
2. Micro quizzes which test users with 5-7 visual multiple choice questions related to the topic.
3. Recommendations units which show related entities like films, books, people, and apps to the topic for users to explore further.Maester The First Platform for Lead Generation on Mobile
Maester The First Platform for Lead Generation on MobileYury Lifshits
油
Maester is build on San Francisco B2B Startup Weekend.
Want to use it to get new leads from mobile? Ping Yury at yury@yury.nameMore Related Content
Similar to Cobinatorial Algorithms for Nearest Neighbors, Near-Duplicates and Small World Design - Yury Lifshits - SODA 2009 (20)
Simulation Informatics; Analyzing Large Scientific Datasets
Simulation Informatics; Analyzing Large Scientific DatasetsDavid Gleich
油
1) The document discusses using large datasets from scientific simulations to analyze uncertainty quantification (UQ) through techniques like randomized parameter studies and reduced order modeling.
2) The author presents work using PageRank as a test case for examining UQ and developing generalized methods for studying parameterized matrix equations.
3) The approach involves constructing an interpolating reduced order model from an ensemble of pre-computed simulation runs stored in a data cluster to enable engineers to efficiently query simulation data for statistical analysis and UQ studies without running new expensive simulations.Drugs and Electrons
Drugs and ElectronsDavid Thompson
油
The document discusses the author's work using computational chemistry methods to develop new drugs through structure-based drug design, explores information theoretic properties of confined electronic systems, and proposes a novel 3D quantum mechanics-based structural descriptor called Sr that could be used for molecular similarity comparisons based on approximating the electron density distribution.Nelly Litvak Asymptotic behaviour of ranking algorithms in directed random ...
Nelly Litvak Asymptotic behaviour of ranking algorithms in directed random ...Yandex
油
There is a vast empirical research on the behaviour of ranking algorithms, e.g. Google PageRank, in scale-free networks. In this talk, we address this problem by analytical probabilistic methods. In particular, it is well-known that the PageRank in scale-free networks follows a power law with the same exponent as in-degree. Recent probabilistic analysis has provided an explanation for this phenomenon by obtaining a natural approximation for PageRank based on stochastic fixed-point equations. For these equations, explicit solutions can be constructed on weighted branching trees, and their tail behavior can be described in great detail.
In this talk we present a model for generating directed random graphs with prescribed degree distributions where we can prove that the PageRank of a randomly chosen node does indeed converge to the solution of the corresponding fixed-point equation as the number of nodes in the graph grows to infinity. The proof of this result is based on classical random graph coupling techniques combined with the now extensive literature on the behavior of branching recursions on trees.Class 11: Deeper List Procedures
Class 11: Deeper List ProceduresDavid Evans
油
list-accumulate vs. list-cruncher
The Story so Far: Recursive Definitions, Universality, Abstraction
Problem Set 3: L-System FractalsPertemuan 5_Relation Matriks_01 (17)
Pertemuan 5_Relation Matriks_01 (17)Evert Sandye Taasiringan
油
The document discusses relations and their application to databases in the relational data model. It defines binary and n-ary relations, and explains how databases can be represented as n-ary relations with records as n-tuples consisting of fields. Primary keys are introduced as fields that uniquely identify each record. Common relational operations like projection and join are explained, with examples provided to illustrate how they transform relations.Computing Local and Global Centrality
Computing Local and Global CentralityDavid Gleich
油
Some recent results on computing PageRank and Katz scores on large networks that I presented at a Dagstuhl workshop.A Primer on Entity Resolution
A Primer on Entity ResolutionBenjamin Bengfort
油
Entity Resolution is the task of disambiguating manifestations of real world entities through linking and grouping and is often an essential part of the data wrangling process. There are three primary tasks involved in entity resolution: deduplication, record linkage, and canonicalization; each of which serve to improve data quality by reducing irrelevant or repeated data, joining information from disparate records, and providing a single source of information to perform analytics upon. However, due to data quality issues (misspellings or incorrect data), schema variations in different sources, or simply different representations, entity resolution is not a straightforward process and most ER techniques utilize machine learning and other stochastic approaches.Prolog Cpt114 - Week 2
Prolog Cpt114 - Week 2a_akhavan
油
This document discusses Prolog and provides examples of:
- Defining facts and rules to represent relationships like parent/child
- Using recursion to define indirect relationships like being a predecessor to someone
- Using path/2 to recursively find all paths between two nodes through arcs
It gives examples of queries to find paths between nodes in a graph.Fast matrix primitives for ranking, link-prediction and more
Fast matrix primitives for ranking, link-prediction and moreDavid Gleich
油
This document summarizes a presentation about fast matrix computations and their applications. It discusses using matrix methods to solve problems related to recommendation systems, network analysis, and ranking aggregation more efficiently. Specific algorithms discussed include PageRank, heat kernels, and nuclear norm ranking. It also describes theoretical guarantees for localization and runtime of these algorithms, as well as empirical evaluations demonstrating their accuracy and performance on real-world datasets.Introduction to Probabilistic Latent Semantic Analysis
Introduction to Probabilistic Latent Semantic AnalysisNYC Predictive Analytics
油
The document provides an introduction to Probabilistic Latent Semantic Analysis (PLSA). It discusses how PLSA improves on previous Latent Semantic Analysis methods by incorporating a probabilistic framework. PLSA models documents as mixtures of topics and allows words to have multiple meanings. The parameters of the PLSA model, including the topic distributions and word-topic distributions, are estimated using an expectation-maximization algorithm to find the parameters that best explain the observed word-document co-occurrence data.CVPR2010: higher order models in computer vision: Part 1, 2
CVPR2010: higher order models in computer vision: Part 1, 2zukun
油
This document discusses tractable higher order models in computer vision using random field models. It introduces Markov random fields (MRFs) and factor graphs as graphical models for computer vision problems. Higher order models that include factors over cliques of more than two variables can model problems more accurately but are generally intractable. The document discusses various inference techniques for higher order models such as relaxation, message passing, and decomposition methods. It provides examples of how higher order and global models can be used in problems like segmentation, stereo matching, reconstruction, and denoising.際際滷s4
際際滷s4BioinformaticsInstitute
油
GraphClust is an alignment-free method for clustering RNA sequences based on their secondary structures. It represents RNA secondary structures as labeled graphs and uses a graph kernel called NSPDK to compute similarities between graphs. GraphClust clusters RNAs in a linear time complexity by using MinHash to identify candidate neighborhoods for clustering, then refines clusters with sequence-structure alignment tools. It was able to cluster hundreds of thousands of RNA sequences in under a month, while traditional alignment-based methods would take hundreds of computer years for the same task.Anti-differentiating Approximation Algorithms: PageRank and MinCut
Anti-differentiating Approximation Algorithms: PageRank and MinCutDavid Gleich
油
We study how Google's PageRank method relates to mincut and a particular type of electrical flow in a network. We also explain the details of how the "push method" for computing PageRank helps to accelerate it. This has implications for semi-supervised learning and machine learning, as well as social network analysis.Spectral graph theory
Spectral graph theoryDanushka Bollegala
油
Spectral clustering works by creating an affinity matrix from a similarity matrix and then applying dimensionality reduction before clustering in the reduced space. It represents the data as an undirected graph and uses the graph Laplacian matrix to perform the dimensionality reduction. The number of clusters can be determined using the eigengap heuristic or by setting k equal to the logarithm of the number of data points. The Gaussian kernel is commonly used to create the affinity matrix from the similarity matrix.[ICDE 2012] On Top-k Structural Similarity Search
[ICDE 2012] On Top-k Structural Similarity SearchPei Lee
油
In this talk, we talk about the following classic problem: given a node in a graph, how can we efficiently track the top-k similar nodes regarding this node, by simply checking the graph link structure? This talk is accompanying with the ICDE 2012 paper "On Top-k Structural Similarity Search", which can be found at http://www.cs.ubc.ca/~peil/research.htmlSimilarity Search in High Dimensions via Hashing
Similarity Search in High Dimensions via HashingMaruf Aytekin
油
This document discusses locality-sensitive hashing (LSH) for similarity search in high dimensions. It introduces LSH as a technique to "hash" similar items to the same bucket with high probability. Locality-sensitive functions are defined that map similar items to the same value more often than dissimilar items. The banding technique divides the data into bands to improve performance. LSH families are described for cosine similarity. Applications include near neighbor search, entity resolution, and matching fingerprints or articles.MUMS Opening Workshop - Emulators for models and Complexity Reduction - Akil ...
MUMS Opening Workshop - Emulators for models and Complexity Reduction - Akil ...The Statistical and Applied Mathematical Sciences Institute
油
The document discusses emulators, which are used to approximate complex models. Emulators take the form of a linear combination of basis functions fitted to available data. Two types of emulators are discussed: linear approximations, where the basis functions are fixed beforehand, and nonlinear approximations, where the basis functions depend on the data. Experimental design for collecting data is critical for building an accurate emulator.pres_coconat
pres_coconatGabriel Gaudreault
油
Gabriel Gaudreault presents a functional calculus called 了-calculus for doing semantics with pregroup grammars. The calculus allows functional composition as the main reduction operation and respects the incoming direction of inputs. There is a 1-1 correspondence between the calculus and a subset of pregroup grammars relevant for linguistic analysis. The calculus can be used for syntactic and semantic analysis of natural language examples. Future work includes further analysis of the semantic power of the calculus and proving properties like Church-Rosser.Chapter 10 link prediction
Chapter 10 link predictionAbanobZakaria1
油
This document discusses link prediction using graph neural networks. It begins with an introduction to link prediction and traditional methods like heuristics and latent feature models. It then discusses how graph neural networks can be used for link prediction, including node-based methods like graph autoencoders that learn node embeddings, and subgraph-based methods that extract local neighborhoods. The document outlines some popular graph neural network models for link prediction and areas for future work.Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks Christopher Morris
油
This document proposes methods to incorporate higher-order graph properties into graph neural networks (GNNs). It shows that GNNs are as powerful as the 1-dimensional Weisfeiler-Lehman graph isomorphism test for distinguishing graphs, but cannot capture higher-order properties like triangle counts. The document introduces k-dimensional GNNs and hierarchical k-GNNs to learn representations of subgraphs. Experimental results show these methods improve over 1-GNN baselines on graph classification and regression tasks.MUMS Opening Workshop - Emulators for models and Complexity Reduction - Akil ...
MUMS Opening Workshop - Emulators for models and Complexity Reduction - Akil ...The Statistical and Applied Mathematical Sciences Institute
油
More from Yury Lifshits (17)
Osh Curiosity Learning on Mobile
Osh Curiosity Learning on MobileYury Lifshits
油
The document describes different types of learning units available in the Osh learning app, including:
1. Streams which allow users to choose topics and scroll through cards with images, short texts, and facts to learn.
2. Micro quizzes which test users with 5-7 visual multiple choice questions related to the topic.
3. Recommendations units which show related entities like films, books, people, and apps to the topic for users to explore further.Maester The First Platform for Lead Generation on Mobile
Maester The First Platform for Lead Generation on MobileYury Lifshits
油
Maester is build on San Francisco B2B Startup Weekend.
Want to use it to get new leads from mobile? Ping Yury at yury@yury.name
Evolution of Two Sided Markets - Yury Lifshits - WSDM 2010
Evolution of Two Sided Markets - Yury Lifshits - WSDM 2010Yury Lifshits
油
This document summarizes research on the evolution of two-sided markets. It presents models of how market shares converge over time based on attachment curves that represent preferential attachment. The models analyze scenarios with independent platforms and platforms forming coalitions. Key results include theorems showing market shares remain stable and conditions where coalitions are profitable for platforms. Open research questions are discussed around predicting market dynamics, stability of models with noise, and investment strategies.New Advertising
New AdvertisingYury Lifshits
油
The document outlines a concept called "New Advertising" which aims to create a more collaborative environment between businesses and consumers. It discusses prototyping a project called "Shopping2.ru" which allows users to search for products, discover new items, and share information. Finally, it proposes a research agenda to collect large datasets of user preferences, develop advanced recommendation systems, and explore issues around data licensing and content curation.Interfaces of Attention: What if people will outsource management of their at...
Interfaces of Attention: What if people will outsource management of their at...Yury Lifshits
油
The document discusses human operating systems and attention interfaces for information distribution. It describes how people consume large amounts of data from various sources and outlines challenges in discovery, filtering and avoiding information overload. It then presents ideas for presentation interfaces like streams and tabs to organize information. Finally, it proposes prototyping reception interfaces that consider size, structure and reputation to determine what information to receive.Data Cloud - Yury Lifshits - Yahoo! Research
Data Cloud - Yury Lifshits - Yahoo! ResearchYury Lifshits
油
In this talk we address two questions:
1) How to use structured data in web search?
2) How to gather structured data?
For the first question we identify valuable classes of data, present query classes that can benefit from structured data and describe architecture that combines keyword search with structured search.
For the second question we present Data Cloud: An ecosystem of data publishers, search engine (data cloud) and data consumers. We show connection form Data Cloud Strategy to classic notion in economics: network effect in two-sided markets. At the end of the talk an early demo implementation will be presented.Future of Search | Yury Lifshits, Yahoo! Research
Future of Search | Yury Lifshits, Yahoo! ResearchYury Lifshits
油
Yury Lifshits presented on the future of search at Yahoo. He discussed structured search which brings structured data to search users. This includes real-time data, semi-private data, and structured queries. He also discussed SearchMonkey which is an open platform that uses structured data to build more useful search results. Additionally, he covered BOSS (Build Your Own Search Service) which allows third parties to build custom search experiences through Yahoo's APIs."Economics of Web Design" by Yury Lifshits
"Economics of Web Design" by Yury LifshitsYury Lifshits
油
This document contains a presentation on web design economics. It discusses an "Anti-AdWords Theorem" which states that under a proposed mathematical model, the design of Google AdWords that separates organic and advertising search results can be "stupid" and improved by another presentation that increases both relevance and revenue. It also covers dynamic design and increasing key numbers for owners and users, and proposes a project to build a hit counter analysis tool.Social Design (Stanford version)
Social Design (Stanford version)Yury Lifshits
油
The document outlines a research agenda for social design. It begins with examples of social design failures and patterns observed in social networks and platforms. It then discusses ideas for new types of data markets and incentive structures. The final section prioritizes areas for further research, including fighting spam, developing new business models, designing for specific domains, implementing wishlists, improving reputation and review systems, providing incentives for the semantic web, and applying social design to academia.Social Design
Social DesignYury Lifshits
油
Social design is the study of designing rules for social systems to achieve specific outcomes, even when individuals act in their own self-interest. It involves setting rules for social mechanisms and systems. The presentation introduces social design as a new field and discusses notable existing social mechanisms as well as new ideas for social design.The Architecture of the Web
The Architecture of the WebYury Lifshits
油
The document provides an outline for a presentation on the architecture of the web. The presentation will include a brief tour of web standards, discussion of conceptual aspects of the web, and an ongoing project about better online marketing. It notes that the traditional definition of the web as a system of interlinked hypertext documents is now outdated, and proposes an updated definition of the web as a system of data, people and software connected via the internet and mobile networks.Reputation Systems I
Reputation Systems IYury Lifshits
油
The document discusses various reputation systems used online, including HITS and PageRank for ranking web pages based on hyperlink structure, eBay and EigenTrust for calculating trustworthiness in peer-to-peer networks, and VKontakte for determining user reputation on a Russian social network. It provides an overview of how these systems work, such as by modeling random walks on graphs or defining hub and authority scores. The document also outlines some open challenges in reputation systems like spam protection and understanding real-world implementations.Reputation Systems II
Reputation Systems IIYury Lifshits
油
The document discusses several algorithms for reputation and ranking systems on graphs, including blogs and social networks. It begins with discussing the Sybil attack and SybilGuard for detecting such attacks. It then covers algorithms for ranking blogs like BlogRank, B2Rank, and EigenRumor that take into account factors like blog activity, links, and comments. MailRank and TrustRank are discussed for using reputation propagation and spam scores to detect spam. The challenges of building measurable and dynamic reputation systems that avoid an arms race are also summarized.Business-Consumer Networks: Concept and Challenges
Business-Consumer Networks: Concept and ChallengesYury Lifshits
油
The document proposes a new web technology called Business-Consumer Networks that would serve as a universal environment for business-consumer communication. It outlines seven principles for the technology, including separating business and private interactions, providing businesses with online identities, merging existing business-focused networks, and using artificial intelligence and reputation-based algorithms. The document also discusses potential functionalities, research challenges, and calls for participation in developing a prototype.Business-Consumer Networks. Project Proposal by Yury Lifshits
Business-Consumer Networks. Project Proposal by Yury LifshitsYury Lifshits
油
The document proposes a new web technology called Business-Consumer Networks that would serve as a universal tool for business-consumer communication. It outlines the goal of designing such a system over 3 months and proposes ideas for key aspects including social design, information architecture, implementation issues, and algorithms. The document encourages participation in the project and discussion of ideas to help design and launch this new business-focused social network.Recently uploaded (20)
THE BIG TEN BIOPHARMACEUTICAL MNCs: GLOBAL CAPABILITY CENTERS IN INDIA
THE BIG TEN BIOPHARMACEUTICAL MNCs: GLOBAL CAPABILITY CENTERS IN INDIASrivaanchi Nathan
油
This business intelligence report, "The Big Ten Biopharmaceutical MNCs: Global Capability Centers in India", provides an in-depth analysis of the operations and contributions of the Global Capability Centers (GCCs) of ten leading biopharmaceutical multinational corporations in India. The report covers AstraZeneca, Bayer, Bristol Myers Squibb, GlaxoSmithKline (GSK), Novartis, Sanofi, Roche, Pfizer, Novo Nordisk, and Eli Lilly. In this report each company's GCC is profiled with details on location, workforce size, investment, and the strategic roles these centers play in global business operations, research and development, and information technology and digital innovation.Fl studio crack version 12.9 Free Download
Fl studio crack version 12.9 Free Downloadkherorpacca127
油
Google the copied link 嶧 https://activationskey.com/download-latest-setup/
嶧
The ultimate guide to FL Studio 12.9 Crack, the revolutionary digital audio workstation that empowers musicians and producers of all levels. This software has become a cornerstone in the music industry, offering unparalleled creative capabilities, cutting-edge features, and an intuitive workflow.
With FL Studio 12.9 Crack, you gain access to a vast arsenal of instruments, effects, and plugins, seamlessly integrated into a user-friendly interface. Its signature Piano Roll Editor provides an exceptional level of musical expression, while the advanced automation features empower you to create complex and dynamic compositions.SMART SENTRY CYBER THREAT INTELLIGENCE IN IIOT
SMART SENTRY CYBER THREAT INTELLIGENCE IN IIOTTanmaiArni
油
SMART SENTRY CYBER THREAT INTELLIGENCE IN IIOTL01 Introduction to Nanoindentation - What is hardness
L01 Introduction to Nanoindentation - What is hardnessRostislavDaniel
油
Introduction to Nanoindentation
UiPath Agentic Automation Capabilities and Opportunities
UiPath Agentic Automation Capabilities and OpportunitiesDianaGray10
油
Learn what UiPath Agentic Automation capabilities are and how you can empower your agents with dynamic decision making. In this session we will cover these topics:
What do we mean by Agents
Components of Agents
Agentic Automation capabilities
What Agentic automation delivers and AI Tools
Identifying Agent opportunities
If you have any questions or feedback, please refer to the "Women in Automation 2025" dedicated Forum thread. You can find there extra details and updates.DealBook of Ukraine: 2025 edition | AVentures Capital
DealBook of Ukraine: 2025 edition | AVentures CapitalYevgen Sysoyev
油
The DealBook is our annual overview of the Ukrainian tech investment industry. This edition comprehensively covers the full year 2024 and the first deals of 2025. Transform Your Future with Front-End Development Training
Transform Your Future with Front-End Development TrainingVtechlabs
油
Kickstart your career in web development with our front-end web development course in Vadodara. Learn HTML, CSS, JavaScript, React, and more through hands-on projects and expert mentorship. Our front-end development course with placement includes real-world training, mock interviews, and job assistance to help you secure top roles like Front-End Developer, UI/UX Developer, and Web Designer.
Join VtechLabs today and build a successful career in the booming IT industry!The Future of Repair: Transparent and Incremental by Botond Denes
The Future of Repair: Transparent and Incremental by Botond DenesScyllaDB
油
Regularly run repairs are essential to keep clusters healthy, yet having a good repair schedule is more challenging than it should be. Repairs often take a long time, preventing running them often. This has an impact on data consistency and also limits the usefulness of the new repair based tombstone garbage collection. We want to address these challenges by making repairs incremental and allowing for automatic repair scheduling, without relying on external tools.Gojek Clone Multi-Service Super App.pptx
Gojek Clone Multi-Service Super App.pptxV3cube
油
Gojek Clone is a versatile multi-service super app that offers ride-hailing, food delivery, payment services, and more, providing a seamless experience for users and businesses alike on a single platform.Future-Proof Your Career with AI Options
Future-Proof Your Career with AI OptionsDianaGray10
油
Learn about the difference between automation, AI and agentic and ways you can harness these to further your career. In this session you will learn:
Introduction to automation, AI, agentic
Trends in the marketplace
Take advantage of UiPath training and certification
In demand skills needed to strategically position yourself to stay ahead
If you have any questions or feedback, please refer to the "Women in Automation 2025" dedicated Forum thread. You can find there extra details and updates.Backstage Software Templates for Java Developers
Backstage Software Templates for Java DevelopersMarkus Eisele
油
As a Java developer you might have a hard time accepting the limitations that you feel being introduced into your development cycles. Let's look at the positives and learn everything important to know to turn Backstag's software templates into a helpful tool you can use to elevate the platform experience for all developers.Formal Methods: Whence and Whither? [Martin Fr辰nzle Festkolloquium, 2025]![Formal Methods: Whence and Whither? [Martin Fr辰nzle Festkolloquium, 2025]](https://cdn.slidesharecdn.com/ss_thumbnails/mf2025-250305164811-a0930761-thumbnail.jpg?width=560&fit=bounds)
Formal Methods: Whence and Whither? [Martin Fr辰nzle Festkolloquium, 2025]Jonathan Bowen
油
Alan Turing arguably wrote the first paper on formal methods 75 years ago. Since then, there have been claims and counterclaims about formal methods. Tool development has been slow but aided by Moores Law with the increasing power of computers. Although formal methods are not widespread in practical usage at a heavyweight level, their influence as crept into software engineering practice to the extent that they are no longer necessarily called formal methods in their use. In addition, in areas where safety and security are important, with the increasing use of computers in such applications, formal methods are a viable way to improve the reliability of such software-based systems. Their use in hardware where a mistake can be very costly is also important. This talk explores the journey of formal methods to the present day and speculates on future directions.
FinTech - US Annual Funding Report - 2024.pptx
FinTech - US Annual Funding Report - 2024.pptxTracxn
油
US FinTech 2024, offering a comprehensive analysis of key trends, funding activities, and top-performing sectors that shaped the FinTech ecosystem in the US 2024. The report delivers detailed data and insights into the region's funding landscape and other developments. We believe this report will provide you with valuable insights to understand the evolving market dynamics.Brave Browser Crack 1.45.133 Activated 2025
Brave Browser Crack 1.45.133 Activated 2025kherorpacca00126
油
https://ncracked.com/7961-2/
Note: >> Please copy the link and paste it into Google New Tab now Download link
Brave is a free Chromium browser developed for Win Downloads, macOS and Linux systems that allows users to browse the internet in a safer, faster and more secure way than its competition. Designed with security in mind, Brave automatically blocks ads and trackers which also makes it faster,
As Brave naturally blocks unwanted content from appearing in your browser, it prevents these trackers and pop-ups from slowing Download your user experience. It's also designed in a way that strips Downloaden which data is being loaded each time you use it. Without these components
Replacing RocksDB with ScyllaDB in Kafka Streams by Almog Gavra
Replacing RocksDB with ScyllaDB in Kafka Streams by Almog GavraScyllaDB
油
Learn how Responsive replaced embedded RocksDB with ScyllaDB in Kafka Streams, simplifying the architecture and unlocking massive availability and scale. The talk covers unbundling stream processors, key ScyllaDB features tested, and lessons learned from the transition.Wondershare Dr.Fone Crack Free Download 2025
Wondershare Dr.Fone Crack Free Download 2025maharajput103
油
copy & paste もゐ https://filedownloadx.com/download-link/
Wondershare Dr.Fone Crack is a comprehensive mobile phone management and recovery software designed to help users recover lost data, repair system issues, and manage mobile devices. It supports both Android and iOS platforms, offering a wide range of features aimed at restoring files, repairing software problems, and backing up or transferring data.UiPath Automation Developer Associate Training Series 2025 - Session 1
UiPath Automation Developer Associate Training Series 2025 - Session 1DianaGray10
油
Welcome to UiPath Automation Developer Associate Training Series 2025 - Session 1.
In this session, we will cover the following topics:
Introduction to RPA & UiPath Studio
Overview of RPA and its applications
Introduction to UiPath Studio
Variables & Data Types
Control Flows
You are requested to finish the following self-paced training for this session:
Variables, Constants and Arguments in Studio 2 modules - 1h 30m - https://academy.uipath.com/courses/variables-constants-and-arguments-in-studio
Control Flow in Studio 2 modules - 2h 15m - https:/academy.uipath.com/courses/control-flow-in-studio
鏝 For any questions you may have, please use the dedicated Forum thread. You can tag the hosts and mentors directly and they will reply as soon as possible. Technology use over time and its impact on consumers and businesses.pptx
Technology use over time and its impact on consumers and businesses.pptxkaylagaze
油
In this presentation, I explore how technology has changed consumer behaviour and its impact on consumers and businesses. I will focus on internet access, digital devices, how customers search for information and what they buy online, video consumption, and lastly consumer trends.World Information Architecture Day 2025 - UX at a Crossroads
World Information Architecture Day 2025 - UX at a CrossroadsJoshua Randall
油
User Experience stands at a crossroads: will we live up to our potential to design a better world? or will we be co-opted by product management or another business buzzword?
Looking backwards, this talk will show how UX has repeatedly failed to create a better world, drawing on industry data from Nielsen Norman Group, Baymard, MeasuringU, WebAIM, and others.
Looking forwards, this talk will argue that UX must resist hype, say no more often and collaborate less often (you read that right), and become a true profession in order to be able to design a better world.