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07/18/2023
Scaling Laws for Imitation Learning in NetHack
Imitation Learning (IL) is one of the most widely used methods in machin...
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10/06/2022
Deep Inventory Management
We present a Deep Reinforcement Learning approach to solving a periodic ...
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12/14/2021
A Framework for the Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data
A central obstacle in the objective assessment of treatment effect (TE) ...
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02/15/2021
Top-k eXtreme Contextual Bandits with Arm Hierarchy
Motivated by modern applications, such as online advertisement and recom...
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10/16/2019
Dynamic Local Regret for Non-convex Online Forecasting
We consider online forecasting problems for non-convex machine learning ...
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05/28/2019
Deep Factors for Forecasting
Producing probabilistic forecasts for large collections of similar and/o...
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11/13/2018
A Local Regret in Nonconvex Online Learning
We consider an online learning process to forecast a sequence of outcome...
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11/13/2017
Invariances and Data Augmentation for Supervised Music Transcription
This paper explores a variety of models for frame-based music transcript...
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01/20/2016
Semantic Word Clusters Using Signed Normalized Graph Cuts
Vector space representations of words capture many aspects of word simil...
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06/26/2015