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06/24/2023
Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective
Graph neural networks (GNNs) have pioneered advancements in graph repres...
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06/20/2023
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks
We study the implicit bias of batch normalization trained by gradient de...
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05/30/2023
Grammar Prompting for Domain-Specific Language Generation with Large Language Models
Large language models (LLMs) can learn to perform a wide range of natura...
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05/17/2023
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Language models are increasingly being deployed for general problem solv...
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02/24/2023
MUX-PLMs: Pre-training Language Models with Data Multiplexing
Data multiplexing is a recently proposed method for improving a model's ...
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08/21/2022
Multiple Descent in the Multiple Random Feature Model
Recent works have demonstrated a double descent phenomenon in over-param...
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07/14/2019
An efficient method to construct self-dual cyclic codes of length p^s over F_p^m+uF_p^m
Let p be an odd prime number, F_p^m be a finite field of cardinality p^m...
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02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
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09/21/2018
High Temperature Structure Detection in Ferromagnets
This paper studies structure detection problems in high temperature ferr...
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08/16/2018
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
Adaptive gradient methods are workhorses in deep learning. However, the ...
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03/03/2018
