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07/26/2023
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models
The quality of training data impacts the performance of pre-trained larg...
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07/20/2023
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
Recent work has shown that language models' (LMs) prompt-based learning ...
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06/13/2023
TART: A plug-and-play Transformer module for task-agnostic reasoning
Large language models (LLMs) exhibit in-context learning abilities which...
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02/23/2023
Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws
Specifying reward functions for complex tasks like object manipulation o...
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01/23/2023
Congested Bandits: Optimal Routing via Short-term Resets
For traffic routing platforms, the choice of which route to recommend to...
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12/09/2022
On the Sensitivity of Reward Inference to Misspecified Human Models
Inferring reward functions from human behavior is at the center of value...
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10/05/2022
Ask Me Anything: A simple strategy for prompting language models
Large language models (LLMs) transfer well to new tasks out-of-the-box s...
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01/10/2022
The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models
Reward hacking – where RL agents exploit gaps in misspecified reward fun...
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05/05/2021
Preference learning along multiple criteria: A game-theoretic perspective
The literature on ranking from ordinal data is vast, and there are sever...
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04/17/2021
Agnostic learning with unknown utilities
Traditional learning approaches for classification implicitly assume tha...
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12/03/2020
Online learning with dynamics: A minimax perspective
We study the problem of online learning with dynamics, where a learner i...
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07/27/2019
Bayesian Robustness: A Nonasymptotic Viewpoint
We study the problem of robustly estimating the posterior distribution f...
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03/19/2019
Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression
We study the problem of robust linear regression with response variable ...
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01/08/2019
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network
This paper develops the FastRNN and FastGRNN algorithms to address the t...
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12/20/2018
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
We study derivative-free methods for policy optimization over the class ...
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11/20/2018
Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation
In this paper, we study the problems of principal Generalized Eigenvecto...
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10/18/2018
Establishing Appropriate Trust via Critical States
In order to effectively interact with or supervise a robot, humans need ...
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07/01/2016
Efficient and Consistent Robust Time Series Analysis
We study the problem of robust time series analysis under the standard a...
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06/08/2015
