Search Results for author: Yang Yuan

Found 39 papers, 17 papers with code

CatCode: A Comprehensive Evaluation Framework for LLMs On the Mixture of Code and Text

no code implementations4 Mar 2024 Zhenru Lin, Yiqun Yao, Yang Yuan

Large language models (LLMs) such as ChatGPT are increasingly proficient in understanding and generating a mixture of code and text.

Code Translation

Autonomous Data Selection with Language Models for Mathematical Texts

2 code implementations12 Feb 2024 Yifan Zhang, Yifan Luo, Yang Yuan, Andrew Chi-Chih Yao

Our method showcases a 2 times increase in pretraining token efficiency compared to state-of-the-art baselines, underscoring the potential of our approach in enhancing models' mathematical reasoning capabilities.

Continual Pretraining GSM8K +3

Meta Prompting for AI Systems

1 code implementation20 Nov 2023 Yifan Zhang, Yang Yuan, Andrew Chi-Chih Yao

In this work, we present a comprehensive study of Meta Prompting (MP), an innovative technique reshaping the utilization of language models (LMs) and AI systems in problem-solving and data interaction.

Data Interaction GSM8K +2

Information Flow in Self-Supervised Learning

2 code implementations29 Sep 2023 Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan, Yifan Zhang

In this paper, we conduct a comprehensive analysis of two dual-branch (Siamese architecture) self-supervised learning approaches, namely Barlow Twins and spectral contrastive learning, through the lens of matrix mutual information.

Contrastive Learning Self-Supervised Learning

Cumulative Reasoning with Large Language Models

1 code implementation8 Aug 2023 Yifan Zhang, Jingqin Yang, Yang Yuan, Andrew Chi-Chih Yao

We demonstrate CR's superiority through several complex reasoning tasks: it outperforms existing methods in logical inference tasks with up to a 9. 3% improvement, achieving 98. 04% accuracy on the curated FOLIO wiki dataset.

Decision Making Logical Reasoning +2

Matrix Information Theory for Self-Supervised Learning

3 code implementations27 May 2023 Yifan Zhang, Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan

Inspired by this framework, we introduce Matrix-SSL, a novel approach that leverages matrix information theory to interpret the maximum entropy encoding loss as matrix uniformity loss.

Contrastive Learning GSM8K +5

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

1 code implementation17 May 2023 Yifan Zhang, Jingqin Yang, Zhiquan Tan, Yang Yuan

Semi-supervised learning has achieved notable success by leveraging very few labeled data and exploiting the wealth of information derived from unlabeled data.

Semi-Supervised Image Classification

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

1 code implementation2 May 2023 Chenzhuang Du, Jiaye Teng, Tingle Li, Yichen Liu, Tianyuan Yuan, Yue Wang, Yang Yuan, Hang Zhao

We abstract the features (i. e. learned representations) of multi-modal data into 1) uni-modal features, which can be learned from uni-modal training, and 2) paired features, which can only be learned from cross-modal interactions.

Contrastive Learning Is Spectral Clustering On Similarity Graph

1 code implementation27 Mar 2023 Zhiquan Tan, Yifan Zhang, Jingqin Yang, Yang Yuan

Contrastive learning is a powerful self-supervised learning method, but we have a limited theoretical understanding of how it works and why it works.

Clustering Contrastive Learning +1

Succinct Representations for Concepts

no code implementations1 Mar 2023 Yang Yuan

Foundation models like chatGPT have demonstrated remarkable performance on various tasks.


On the Power of Foundation Models

no code implementations29 Nov 2022 Yang Yuan

The second one says fine tuning does not have this limit, as a foundation model with the minimum required power (up to symmetry) can theoretically solve downstream tasks for the category defined by pretext task, with fine tuning and enough resources.

Self-Supervised Learning

Anomaly Detection with Test Time Augmentation and Consistency Evaluation

no code implementations6 Jun 2022 Haowei He, Jiaye Teng, Yang Yuan

Deep neural networks are known to be vulnerable to unseen data: they may wrongly assign high confidence stcores to out-distribuion samples.

Anomaly Detection Representation Learning

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

1 code implementation8 Mar 2021 Jiaye Teng, Zeren Tan, Yang Yuan

It is challenging to deal with censored data, where we only have access to the incomplete information of survival time instead of its exact value.

Imbalance Robust Softmax for Deep Embeeding Learning

no code implementations23 Nov 2020 Hao Zhu, Yang Yuan, Guosheng Hu, Xiang Wu, Neil Robertson

IR-Softmax can generalise to any softmax and its variants (which are discriminative for open-set problem) by directly setting the weights as their class centers, naturally solving the data imbalance problem.

Face Recognition Person Re-Identification

Secure Data Sharing With Flow Model

1 code implementation24 Sep 2020 Chenwei Wu, Chenzhuang Du, Yang Yuan

In the classical multi-party computation setting, multiple parties jointly compute a function without revealing their own input data.

BIG-bench Machine Learning Image Classification +1

Inject Machine Learning into Significance Test for Misspecified Linear Models

no code implementations4 Jun 2020 Jiaye Teng, Yang Yuan

First, we apply a machine learning method to fit the ground truth function on the training set and calculate its linear approximation.

BIG-bench Machine Learning regression

Learning-Based Low-Rank Approximations

no code implementations NeurIPS 2019 Piotr Indyk, Ali Vakilian, Yang Yuan

Our experiments show that, for multiple types of data sets, a learned sketch matrix can substantially reduce the approximation loss compared to a random matrix $S$, sometimes by one order of magnitude.

Generalization Bounds

Neural Embeddings for Nearest Neighbor Search Under Edit Distance

no code implementations25 Sep 2019 Xiyuan Zhang, Yang Yuan, Piotr Indyk

The edit distance between two sequences is an important metric with many applications.

$\ell_1$ Adversarial Robustness Certificates: a Randomized Smoothing Approach

no code implementations25 Sep 2019 Jiaye Teng, Guang-He Lee, Yang Yuan

Robustness is an important property to guarantee the security of machine learning models.

Adversarial Robustness

Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers

1 code implementation NeurIPS 2019 Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola

Specifically, an $\ell_2$ bounded adversary cannot alter the ensemble prediction generated by an additive isotropic Gaussian noise, where the radius for the adversary depends on both the variance of the distribution as well as the ensemble margin at the point of interest.

Adversarial Robustness

Asymmetric Valleys: Beyond Sharp and Flat Local Minima

1 code implementation NeurIPS 2019 Haowei He, Gao Huang, Yang Yuan

Specifically, at a local minimum there exist many asymmetric directions such that the loss increases abruptly along one side, and slowly along the opposite side--we formally define such minima as asymmetric valleys.

Expanding Holographic Embeddings for Knowledge Completion

no code implementations NeurIPS 2018 Yexiang Xue, Yang Yuan, Zhitian Xu, Ashish Sabharwal

Neural models operating over structured spaces such as knowledge graphs require a continuous embedding of the discrete elements of this space (such as entities) as well as the relationships between them.

Knowledge Graphs

Hyperparameter Optimization: A Spectral Approach

1 code implementation ICLR 2018 Elad Hazan, Adam Klivans, Yang Yuan

In particular, we obtain the first quasi-polynomial time algorithm for learning noisy decision trees with polynomial sample complexity.

Bayesian Optimization Hyperparameter Optimization

Convergence Analysis of Two-layer Neural Networks with ReLU Activation

no code implementations NeurIPS 2017 Yuanzhi Li, Yang Yuan

We also show that the identity mapping is necessary for convergence, as it moves the initial point to a better place for optimization.

Vocal Bursts Valence Prediction

Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling

no code implementations30 Dec 2015 Zeyuan Allen-Zhu, Zheng Qu, Peter Richtárik, Yang Yuan

Accelerated coordinate descent is widely used in optimization due to its cheap per-iteration cost and scalability to large-scale problems.

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

3 code implementations5 Jun 2015 Zeyuan Allen-Zhu, Yang Yuan

Many classical algorithms are found until several years later to outlive the confines in which they were conceived, and continue to be relevant in unforeseen settings.


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

1 code implementation6 Mar 2015 Rong Ge, Furong Huang, Chi Jin, Yang Yuan

To the best of our knowledge this is the first work that gives global convergence guarantees for stochastic gradient descent on non-convex functions with exponentially many local minima and saddle points.

Tensor Decomposition

Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms

no code implementations31 Jul 2014 Wei Chen, Yajun Wang, Yang Yuan, Qinshi Wang

The objective of an online learning algorithm for CMAB is to minimize (\alpha,\beta)-approximation regret, which is the difference between the \alpha{\beta} fraction of the expected reward when always playing the optimal super arm, and the expected reward of playing super arms according to the algorithm.

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