Weihao Gao | DeepAI

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∙ 06/21/2023

OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and Dialogue

Large multimodal language models (LMMs) have achieved significant succes...

0 Weihao Gao, et al. ∙

∙ 01/28/2022

Learning to Simulate Unseen Physical Systems with Graph Neural Networks

Simulation of the dynamics of physical systems is essential to the devel...

0 Ce Yang, et al. ∙

∙ 11/30/2021

Learning Large-Time-Step Molecular Dynamics with Graph Neural Networks

Molecular dynamics (MD) simulation predicts the trajectory of atoms by s...

0 Tianze Zheng, et al. ∙

∙ 07/21/2021

Defending against Reconstruction Attack in Vertical Federated Learning

Recently researchers have studied input leakage problems in Federated Le...

0 Jiankai Sun, et al. ∙

∙ 06/10/2021

Vertical Federated Learning without Revealing Intersection Membership

Vertical Federated Learning (vFL) allows multiple parties that own diffe...

0 Jiankai Sun, et al. ∙

∙ 04/27/2021

One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning

Deep learning models in large-scale machine learning systems are often c...

0 Chaosheng Dong, et al. ∙

∙ 02/17/2021

Label Leakage and Protection in Two-party Split Learning

In vertical federated learning, two-party split learning has become an i...

0 Oscar Li, et al. ∙

∙ 07/12/2020

Deep Retrieval: An End-to-End Learnable Structure Model for Large-Scale Recommendations

One of the core problems in large-scale recommendations is to retrieve t...

16 Weihao Gao, et al. ∙

∙ 01/27/2019

Information-Theoretic Understanding of Population Risk Improvement with Model Compression

We show that model compression can improve the population risk of a pre-...

0 Yuheng Bu, et al. ∙

∙ 10/09/2018

Rate Distortion For Model Compression: From Theory To Practice

As the size of neural network models increases dramatically today, study...

0 Weihao Gao, et al. ∙

∙ 10/09/2018

Learning One-hidden-layer Neural Networks under General Input Distributions

Significant advances have been made recently on training neural networks...

6 Weihao Gao, et al. ∙

∙ 11/23/2017

The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal

We analyze the Kozachenko--Leonenko (KL) nearest neighbor estimator for ...

0 Jiantao Jiao, et al. ∙

∙ 09/12/2017

Discovering Potential Correlations via Hypercontractivity

Discovering a correlation from one variable to another variable is of fu...

0 Hyeji Kim, et al. ∙

∙ 09/07/2016

Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation

Estimators of information theoretic measures such as entropy and mutual ...

0 Weihao Gao, et al. ∙

∙ 04/11/2016

Demystifying Fixed k-Nearest Neighbor Information Estimators

Estimating mutual information from i.i.d. samples drawn from an unknown ...

0 Weihao Gao, et al. ∙

∙ 02/10/2016

Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications

We conduct an axiomatic study of the problem of estimating the strength ...

0 Weihao Gao, et al. ∙

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