233 citations · 581 across the 28 of their papers we have counts for
7 papers · 1 filter
Reward Weighted Classifier-Free Guidance as Policy Improvement in Autoregressive Models
Alexander Peysakhovich, William Berman
Consider an auto-regressive model that produces outputs x (e.g., answers to questions, molecules) each of which can be summarized by an attribute vector y (e.g., helpfulness vs. ha…
Efficient Heterogeneous Treatment Effect Estimation With Multiple Experiments and Multiple Outcomes
Leon Yao, Caroline Lo, Israel Nir +4
Learning heterogeneous treatment effects (HTEs) is an important problem across many fields. Most existing methods consider the setting with a single treatment arm and a single outc…
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian
Jack Parker-Holder, Luke Metz, Cinjon Resnick +6
Over the last decade, a single algorithm has changed many facets of our lives - Stochastic Gradient Descent (SGD). In the era of ever decreasing loss functions, SGD and its various…
Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions
Tom Yan, Christian Kroer, Alexander Peysakhovich
Can we predict how well a team of individuals will perform together? How should individuals be rewarded for their contributions to the team performance? Cooperative game theory giv…
PyTorch-BigGraph: A Large-scale Graph Embedding System
Adam Lerer, Ledell Wu, Jiajun Shen +4
Graph embedding methods produce unsupervised node features from graphs that can then be used for a variety of machine learning tasks. Modern graphs, particularly in industrial appl…
Discovering Context Effects from Raw Choice Data
Arjun Seshadri, Alexander Peysakhovich, Johan Ugander
Many applications in preference learning assume that decisions come from the maximization of a stable utility function. Yet a large experimental literature shows that individual ch…
Reinforcement Learning and Inverse Reinforcement Learning with System 1 and System 2
Alexander Peysakhovich
Inferring a person's goal from their behavior is an important problem in applications of AI (e.g. automated assistants, recommender systems). The workhorse model for this task is t…