Search Results for author: Yang Yuan

Found 31 papers, 8 papers with code

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 first one limits the power of prompt-based learning, saying that the model can solve a downstream task with prompts if and only if the task is representable.

Self-Supervised Learning

Consistent and Truthful Interpretation with Fourier Analysis

no code implementations31 Oct 2022 Yifan Zhang, Haowei He, Yang Yuan

For many interdisciplinary fields, ML interpretations need to be consistent with what-if scenarios related to the current case, i. e., if one factor changes, how does the model react?

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

When do Models Generalize? A Perspective from Data-Algorithm Compatibility

no code implementations12 Feb 2022 Jing Xu, Jiaye Teng, Yang Yuan, Andrew Chi-Chih Yao

By considering the entire training trajectory and focusing on early-stopping iterates, compatibility exploits the data and the algorithm information and is therefore a more suitable notion for generalization.

Generalization Bounds Learning Theory

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

$\ell_1$ 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

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.

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.

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.

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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