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09/19/2023
Investigating the Catastrophic Forgetting in Multimodal Large Language Models
Following the success of GPT4, there has been a surge in interest in mul...
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03/09/2023
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning
A compelling use case of offline reinforcement learning (RL) is to obtai...
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02/18/2023
Closed-Loop Transcription via Convolutional Sparse Coding
Autoencoding has achieved great empirical success as a framework for lea...
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12/24/2022
Understanding the Complexity Gains of Single-Task RL with a Curriculum
Reinforcement learning (RL) problems can be challenging without well-sha...
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10/18/2022
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity
Reinforcement learning provides an automated framework for learning beha...
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07/08/2021
Computational Benefits of Intermediate Rewards for Hierarchical Planning
Many hierarchical reinforcement learning (RL) applications have empirica...
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03/01/2021
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training
Normalization techniques have become a basic component in modern convolu...
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12/05/2019
Analysis of the Optimization Landscapes for Overcomplete Representation Learning
We study nonconvex optimization landscapes for learning overcomplete rep...
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06/06/2019
Complete Dictionary Learning via â„“^4-Norm Maximization over the Orthogonal Group
This paper considers the fundamental problem of learning a complete (ort...
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05/17/2019
