Yang Yuan | DeepAI

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Featured Co-authors

Yue Wang
263 publications
Peter Richtarik
143 publications
Yu Sun
127 publications
Gao Huang
92 publications
Yifan Zhang
87 publications
Yuanzhi Li
85 publications
Shiyu Chang
81 publications
Hang Zhao
78 publications
Liang Zhang
76 publications
Rong Ge
66 publications
Elad Hazan
65 publications

∙ 08/08/2023

Cumulative Reasoning with Large Language Models

While language models are powerful and versatile, they often fail to add...

0 Yifan Zhang, et al. ∙

∙ 05/27/2023

Kernel-SSL: Kernel KL Divergence for Self-Supervised Learning

Contrastive learning usually compares one positive anchor sample with lo...

0 Yifan Zhang, et al. ∙

∙ 05/17/2023

RelationMatch: Matching In-batch Relationships for Semi-supervised Learning

Semi-supervised learning has achieved notable success by leveraging very...

0 Yifan Zhang, et al. ∙

∙ 05/02/2023

On Uni-Modal Feature Learning in Supervised Multi-Modal Learning

We abstract the features (i.e. learned representations) of multi-modal d...

7 Chenzhuang Du, et al. ∙

∙ 03/27/2023

Contrastive Learning Is Spectral Clustering On Similarity Graph

Contrastive learning is a powerful self-supervised learning method, but ...

0 Zhiquan Tan, et al. ∙

∙ 03/08/2023

A Categorical Framework of General Intelligence

Can machines think? Since Alan Turing asked this question in 1950, nobod...

0 Yang Yuan, et al. ∙

∙ 03/01/2023

Succinct Representations for Concepts

Foundation models like chatGPT have demonstrated remarkable performance ...

0 Yang Yuan, et al. ∙

∙ 11/29/2022

On the power of foundation models

With infinitely many high-quality data points, infinite computational po...

0 Yang Yuan, et al. ∙

∙ 10/31/2022

Consistent and Truthful Interpretation with Fourier Analysis

For many interdisciplinary fields, ML interpretations need to be consist...

0 Yifan Zhang, et al. ∙

∙ 06/06/2022

Anomaly Detection with Test Time Augmentation and Consistency Evaluation

Deep neural networks are known to be vulnerable to unseen data: they may...

0 Haowei He, et al. ∙

∙ 06/11/2021

Towards Understanding Generalization via Decomposing Excess Risk Dynamics

Generalization is one of the critical issues in machine learning. Howeve...

0 Jiaye Teng, et al. ∙

∙ 03/08/2021

T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP

It is challenging to deal with censored data, where we only have access ...

13 Jiaye Teng, et al. ∙

∙ 09/24/2020

Secure Data Sharing With Flow Model

In the classical multi-party computation setting, multiple parties joint...

19 Chenwei Wu, et al. ∙

∙ 06/04/2020

Inject Machine Learning into Significance Test for Misspecified Linear Models

Due to its strong interpretability, linear regression is widely used in ...

0 Jiaye Teng, et al. ∙

∙ 02/10/2020

Adversarial Data Encryption

In the big data era, many organizations face the dilemma of data sharing...

2 Yingdong Hu, et al. ∙

∙ 10/30/2019

Learning-Based Low-Rank Approximations

We introduce a "learning-based" algorithm for the low-rank decomposition...

14 Piotr Indyk, et al. ∙

∙ 07/12/2019

System-Level Development of a User-Integrated Semi-Autonomous Lawn Mowing System: Problem Overview, Basic Requirements, and Proposed Architecture

This concept paper outlines some recent efforts toward the design and de...

0 Albert E. Patterson, et al. ∙

∙ 06/12/2019

A Stratified Approach to Robustness for Randomly Smoothed Classifiers

Strong theoretical guarantees of robustness can be given for ensembles o...

1 Guang-He Lee, et al. ∙

∙ 02/02/2019

Asymmetric Valleys: Beyond Sharp and Flat Local Minima

Despite the non-convex nature of their loss functions, deep neural netwo...

0 Haowei He, et al. ∙

∙ 06/19/2018

An empirical study on evaluation metrics of generative adversarial networks

Evaluating generative adversarial networks (GANs) is inherently challeng...

0 Qiantong Xu, et al. ∙

∙ 02/17/2018

An Alternative View: When Does SGD Escape Local Minima?

Stochastic gradient descent (SGD) is widely used in machine learning. Al...

0 Robert Kleinberg, et al. ∙

∙ 06/02/2017

Hyperparameter Optimization: A Spectral Approach

We give a simple, fast algorithm for hyperparameter optimization inspire...

0 Elad Hazan, et al. ∙

∙ 02/05/2016

Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters

The amount of data available in the world is growing faster than our abi...

0 Zeyuan Allen-Zhu, et al. ∙

∙ 12/30/2015

Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling

Accelerated coordinate descent is widely used in optimization due to its...

0 Zeyuan Allen-Zhu, et al. ∙

∙ 06/05/2015

Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives

Many classical algorithms are found until several years later to outlive...

0 Zeyuan Allen-Zhu, et al. ∙

∙ 03/06/2015

Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition

We analyze stochastic gradient descent for optimizing non-convex functio...

0 Rong Ge, et al. ∙

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