398 citations · 1.7k across the 67 of their papers we have counts for
78 papers
Oracle-Efficient Pessimism: Offline Policy Optimization in Contextual Bandits
Lequn Wang, Akshay Krishnamurthy, Aleksandrs Slivkins
We consider offline policy optimization (OPO) in contextual bandits, where one is given a fixed dataset of logged interactions. While pessimistic regularizers are typically used to…
Exposing Attention Glitches with Flip-Flop Language Modeling
Bingbin Liu, Jordan T. Ash, Surbhi Goel +2
Why do large language models sometimes output factual inaccuracies and exhibit erroneous reasoning? The brittleness of these models, particularly when executing long chains of reas…
Streaming Active Learning with Deep Neural Networks
Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy +2
Active learning is perhaps most naturally posed as an online learning problem. However, prior active learning approaches with deep neural networks assume offline access to the enti…
Learning Hidden Markov Models Using Conditional Samples
Sham M. Kakade, Akshay Krishnamurthy, Gaurav Mahajan +1
This paper is concerned with the computational complexity of learning the Hidden Markov Model (HMM). Although HMMs are some of the most widely used tools in sequential and time ser…
Statistical Learning under Heterogeneous Distribution Shift
Max Simchowitz, Anurag Ajay, Pulkit Agrawal +1
This paper studies the prediction of a target from a pair of random variables , where the ground-truth predictor is additive $\mathbb{E}[\math…
Transformers Learn Shortcuts to Automata
Bingbin Liu, Jordan T. Ash, Surbhi Goel +2
Algorithmic reasoning requires capabilities which are most naturally understood through recurrent models of computation, like the Turing machine. However, Transformer models, while…