Dynamic Time Warping を用いた高頻度取引データのLead-Lag 効果の推定Katsuya Ito
?
This paper investigates the Lead-Lag relationships in high-frequency data.
We propose Multinomial Dynamic Time Warping (MDTW) that deals with non-synchronous observation, vast data, and time-varying Lead-Lag.
MDTW directly estimates the Lead-Lags without lag candidates. Its computational complexity is linear with respect to the number of observation and it does not depend on the number of lag candidates.
The experiments adopting artificial data and market data illustrate the effectiveness of our method compared to the existing methods.
Convex Analysis and Duality (based on "Functional Analysis and Optimization" ...Katsuya Ito
?
This document discusses concepts from functional analysis and optimization, focusing on duality, including primal and dual problems, Lagrangian formulations, and properties of convex functionals. It elaborates on lower-semicontinuity, subdifferentials, and conjugate functionals, as well as their mathematical definitions and examples. The document serves as an introduction to duality theory and related topics in convex analysis.
ICLR 2018 Best papers3本をざっくり紹介したスライドです。
On the convergence of Adam and Beyond
Spherical CNNs
Continuous adaptation via meta-learning in nonstationary and competitive environments
園田翔氏の博士論文を解説しました。
Integral Representation Theory of Deep Neural Networks
深層学習を数学的に定式化して解釈します。
3行でいうと、
ーニューラルネットワーク—(連続化)→双対リッジレット変換
ー双対リッジレット変換=輸送写像
ー輸送写像でNeural Networkを定式化し、解釈する。
目次
ー深層ニューラルネットワークの数学的定式化
ーリッジレット変換について
ー輸送写像について
以下の6つの論文をゼミで紹介した
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Spectral Normalization for Generative Adversarial Networks
cGANs with Projection Discriminator
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
Are GANs Created Equal? A Large-Scale Study
Improved Training of Wasserstein GANs
Protect Your IoT Data with UbiBot's Private Platform.pptxユビボット 株式会社
?
Our on-premise IoT platform offers a secure and scalable solution for businesses, with features such as real-time monitoring, customizable alerts and open API support, and can be deployed on your own servers to ensure complete data privacy and control.
Dynamic Time Warping を用いた高頻度取引データのLead-Lag 効果の推定Katsuya Ito
?
This paper investigates the Lead-Lag relationships in high-frequency data.
We propose Multinomial Dynamic Time Warping (MDTW) that deals with non-synchronous observation, vast data, and time-varying Lead-Lag.
MDTW directly estimates the Lead-Lags without lag candidates. Its computational complexity is linear with respect to the number of observation and it does not depend on the number of lag candidates.
The experiments adopting artificial data and market data illustrate the effectiveness of our method compared to the existing methods.
Convex Analysis and Duality (based on "Functional Analysis and Optimization" ...Katsuya Ito
?
This document discusses concepts from functional analysis and optimization, focusing on duality, including primal and dual problems, Lagrangian formulations, and properties of convex functionals. It elaborates on lower-semicontinuity, subdifferentials, and conjugate functionals, as well as their mathematical definitions and examples. The document serves as an introduction to duality theory and related topics in convex analysis.
ICLR 2018 Best papers3本をざっくり紹介したスライドです。
On the convergence of Adam and Beyond
Spherical CNNs
Continuous adaptation via meta-learning in nonstationary and competitive environments
園田翔氏の博士論文を解説しました。
Integral Representation Theory of Deep Neural Networks
深層学習を数学的に定式化して解釈します。
3行でいうと、
ーニューラルネットワーク—(連続化)→双対リッジレット変換
ー双対リッジレット変換=輸送写像
ー輸送写像でNeural Networkを定式化し、解釈する。
目次
ー深層ニューラルネットワークの数学的定式化
ーリッジレット変換について
ー輸送写像について
以下の6つの論文をゼミで紹介した
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Spectral Normalization for Generative Adversarial Networks
cGANs with Projection Discriminator
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
Are GANs Created Equal? A Large-Scale Study
Improved Training of Wasserstein GANs
Protect Your IoT Data with UbiBot's Private Platform.pptxユビボット 株式会社
?
Our on-premise IoT platform offers a secure and scalable solution for businesses, with features such as real-time monitoring, customizable alerts and open API support, and can be deployed on your own servers to ensure complete data privacy and control.