Search Results
SCQPTH: an efficient differentiable splitting method for convex quadratic programming
We present SCQPTH: a differentiable first-order splitting method for convex quadratic programs.
Evidence of Crowding on Russell 3000 Reconstitution Events
We develop a methodology which replicates in great accuracy the FTSE Russell indexes reconstitutions, including the quarterly rebalancings due to new initial public offerings (IPOs).
An Empirical Study of Capital Asset Pricing Model based on Chinese A-share Trading Data
This paper presents an empirical analysis of the capital asset pricing model using trading data for the Chinese A-share market from 2000 to 2019.
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning
A fundamental challenge in reinforcement learning is to learn policies that generalize beyond the operating domains experienced during training.
Modeling Relational Data with Graph Convolutional Networks
We demonstrate the effectiveness of R-GCNs as a stand-alone model for entity classification.
Ranked #1 on
Node Classification
on AIFB
Gradient boosting for convex cone predict and optimize problems
Prediction models are typically optimized independently from decision optimization.
Social Media Emotions and IPO Returns
I examine potential mechanisms behind two stylized facts of initial public offerings (IPOs) returns.
IPO: Interior-point Policy Optimization under Constraints
In this paper, we study reinforcement learning (RL) algorithms to solve real-world decision problems with the objective of maximizing the long-term reward as well as satisfying cumulative constraints.
iPool -- Information-based Pooling in Hierarchical Graph Neural Networks
In this paper, we propose a parameter-free pooling operator, called iPool, that permits to retain the most informative features in arbitrary graphs.
iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis
There will be distinctive movement, despite evident variations caused by the stochastic nature of our world.
