Tianle Cai | DeepAI

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∙ 07/05/2023

Scaling In-Context Demonstrations with Structured Attention

The recent surge of large language models (LLMs) highlights their abilit...

0 Tianle Cai, et al. ∙

∙ 05/28/2023

Reward Collapse in Aligning Large Language Models

The extraordinary capabilities of large language models (LLMs) such as C...

4 Ziang Song, et al. ∙

∙ 05/26/2023

Large Language Models as Tool Makers

Recent research shows the potential of enhancing the problem-solving abi...

7 Tianle Cai, et al. ∙

∙ 10/17/2022

What Makes Convolutional Models Great on Long Sequence Modeling?

Convolutional models have been widely used in multiple domains. However,...

10 Yuhong Li, et al. ∙

∙ 07/19/2022

Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond

We consider vertical logistic regression (VLR) trained with mini-batch g...

5 Yuzheng Hu, et al. ∙

∙ 06/23/2021

Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding

The attention module, which is a crucial component in Transformer, canno...

9 Shengjie Luo, et al. ∙

∙ 06/15/2021

First Place Solution of KDD Cup 2021 OGB Large-Scale Challenge Graph-Level Track

In this technical report, we present our solution of KDD Cup 2021 OGB La...

7 Chengxuan Ying, et al. ∙

∙ 06/09/2021

Do Transformers Really Perform Bad for Graph Representation?

The Transformer architecture has become a dominant choice in many domain...

16 Chengxuan Ying, et al. ∙

∙ 06/08/2021

Towards a Theoretical Framework of Out-of-Distribution Generalization

Generalization to out-of-distribution (OOD) data, or domain generalizati...

45 Haotian Ye, et al. ∙

∙ 02/22/2021

A Theory of Label Propagation for Subpopulation Shift

One of the central problems in machine learning is domain adaptation. Un...

4 Tianle Cai, et al. ∙

∙ 02/10/2021

Towards Certifying ℓ_∞ Robustness using Neural Networks with ℓ_∞-dist Neurons

It is well-known that standard neural networks, even with a high classif...

2 Bohang Zhang, et al. ∙

∙ 09/22/2020

Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot

Network pruning is a method for reducing test-time computational resourc...

18 Jingtong Su, et al. ∙

∙ 09/07/2020

GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training

Normalization plays an important role in the optimization of deep neural...

1 Tianle Cai, et al. ∙

∙ 07/27/2020

RANDOM MASK: Towards Robust Convolutional Neural Networks

Robustness of neural networks has recently been highlighted by the adver...

20 Tiange Luo, et al. ∙

∙ 06/01/2020

Locally Differentially Private (Contextual) Bandits Learning

We study locally differentially private (LDP) bandits learning in this p...

4 Kai Zheng, et al. ∙

∙ 11/19/2019

Defective Convolutional Layers Learn Robust CNNs

Robustness of convolutional neural networks has recently been highlighte...

20 Tiange Luo, et al. ∙

∙ 06/19/2019

Convergence of Adversarial Training in Overparametrized Networks

Neural networks are vulnerable to adversarial examples, i.e. inputs that...

0 Ruiqi Gao, et al. ∙

∙ 06/03/2019

Adversarially Robust Generalization Just Requires More Unlabeled Data

Neural network robustness has recently been highlighted by the existence...

0 Runtian Zhai, et al. ∙

∙ 05/28/2019

A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems

First-order methods such as stochastic gradient descent (SGD) are curren...

0 Tianle Cai, et al. ∙

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