Search Results for author: Yuchen Zhang

Found 37 papers, 6 papers with code

Kalman-Like Filter under Binary Sensors

no code implementations27 Oct 2021 Zhongyao Hu, Bo Chen, Yuchen Zhang, Li Yu

When considering linear dynamic systems, a conservative estimation error covariance with adjustable parameters is constructed by matrix inequality, and then an optimal filter gain is derived by minimizing its trace.

Vision-Guided Quadrupedal Locomotion in the Wild with Multi-Modal Delay Randomization

no code implementations29 Sep 2021 Chieko Sarah Imai, Minghao Zhang, Yuchen Zhang, Marcin Kierebinski, Ruihan Yang, Yuzhe Qin, Xiaolong Wang

While Reinforcement Learning (RL) provides a promising paradigm for agile locomotion skills with vision inputs in simulation, it is still very challenging to deploy the RL policy in the real world.

Exploring Retraining-Free Speech Recognition for Intra-sentential Code-Switching

no code implementations27 Aug 2021 Zhen Huang, Xiaodan Zhuang, Daben Liu, Xiaoqiang Xiao, Yuchen Zhang, Sabato Marco Siniscalchi

To achieve such an ambitious goal, new mechanisms for foreign pronunciation generation and language model (LM) enrichment have been devised.

Speech Recognition

Value-Agnostic Conversational Semantic Parsing

no code implementations ACL 2021 Emmanouil Antonios Platanios, Adam Pauls, Subhro Roy, Yuchen Zhang, Alexander Kyte, Alan Guo, Sam Thomson, Jayant Krishnamurthy, Jason Wolfe, Jacob Andreas, Dan Klein

Conversational semantic parsers map user utterances to executable programs given dialogue histories composed of previous utterances, programs, and system responses.

Semantic Parsing

Adversarial example generation with AdaBelief Optimizer and Crop Invariance

no code implementations7 Feb 2021 Bo Yang, Hengwei Zhang, Yuchen Zhang, Kaiyong Xu, Jindong Wang

ABI-FGM and CIM can be readily integrated to build a strong gradient-based attack to further boost the success rates of adversarial examples for black-box attacks.

The estimate of sensitivity for large infrared telescopes based on measured sky brightness and atmospheric extinction

no code implementations23 Sep 2020 Zhijun Zhao, Haijing Zhou, Yuchen Zhang, Yun Ling, Fangyu Xu

In order to evaluate the ground-based infrared telescope sensitivity affected by the noise from the atmosphere, instruments and detectors, we construct a sensitivity model that can calculate limiting magnitudes and signal-to-noise ratio ($S/N$).

Instrumentation and Methods for Astrophysics

On Localized Discrepancy for Domain Adaptation

no code implementations14 Aug 2020 Yuchen Zhang, Mingsheng Long, Jian-Min Wang, Michael. I. Jordan

Finally, we further extend the localized discrepancies for achieving super transfer and derive generalization bounds that could be even more sample-efficient on source domain.

Generalization Bounds Unsupervised Domain Adaptation

HPC AI500: A Benchmark Suite for HPC AI Systems

no code implementations27 Jul 2019 Zihan Jiang, Wanling Gao, Lei Wang, Xingwang Xiong, Yuchen Zhang, Xu Wen, Chunjie Luo, Hainan Ye, Yunquan Zhang, Shengzhong Feng, Kenli Li, Weijia Xu, Jianfeng Zhan

In this paper, we propose HPC AI500 --- a benchmark suite for evaluating HPC systems that running scientific DL workloads.

Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study

no code implementations SEMEVAL 2019 Yuchen Zhang, Nianwen Xue

Temporal Dependency Trees are a structured temporal representation that represents temporal relations among time expressions and events in a text as a dependency tree structure.

Bridging Theory and Algorithm for Domain Adaptation

4 code implementations11 Apr 2019 Yuchen Zhang, Tianle Liu, Mingsheng Long, Michael. I. Jordan

We introduce Margin Disparity Discrepancy, a novel measurement with rigorous generalization bounds, tailored to the distribution comparison with the asymmetric margin loss, and to the minimax optimization for easier training.

Domain Adaptation Generalization Bounds

Defending against Whitebox Adversarial Attacks via Randomized Discretization

1 code implementation25 Mar 2019 Yuchen Zhang, Percy Liang

Adversarial perturbations dramatically decrease the accuracy of state-of-the-art image classifiers.

Adversarial Attack General Classification

Neural Ranking Models for Temporal Dependency Structure Parsing

2 code implementations EMNLP 2018 Yuchen Zhang, Nianwen Xue

In a parsing-only evaluation setup where gold time expressions and events are provided, our parser reaches 0. 81 and 0. 70 f-score on unlabeled and labeled parsing respectively, a result that is very competitive against alternative approaches.

Feature Engineering

Structured Interpretation of Temporal Relations

2 code implementations LREC 2018 Yuchen Zhang, Nianwen Xue

Temporal relations between events and time expressions in a document are often modeled in an unstructured manner where relations between individual pairs of time expressions and events are considered in isolation.

Macro Grammars and Holistic Triggering for Efficient Semantic Parsing

2 code implementations EMNLP 2017 Yuchen Zhang, Panupong Pasupat, Percy Liang

To learn a semantic parser from denotations, a learning algorithm must search over a combinatorially large space of logical forms for ones consistent with the annotated denotations.

Semantic Parsing Sentence Similarity

A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics

no code implementations18 Feb 2017 Yuchen Zhang, Percy Liang, Moses Charikar

We study the Stochastic Gradient Langevin Dynamics (SGLD) algorithm for non-convex optimization.

Convexified Convolutional Neural Networks

1 code implementation ICML 2017 Yuchen Zhang, Percy Liang, Martin J. Wainwright

For learning two-layer convolutional neural networks, we prove that the generalization error obtained by a convexified CNN converges to that of the best possible CNN.

Denoising

Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences

no code implementations NeurIPS 2016 Chi Jin, Yuchen Zhang, Sivaraman Balakrishnan, Martin J. Wainwright, Michael Jordan

Our first main result shows that the population likelihood function has bad local maxima even in the special case of equally-weighted mixtures of well-separated and spherical Gaussians.

Learning Halfspaces and Neural Networks with Random Initialization

no code implementations25 Nov 2015 Yuchen Zhang, Jason D. Lee, Martin J. Wainwright, Michael. I. Jordan

For loss functions that are $L$-Lipschitz continuous, we present algorithms to learn halfspaces and multi-layer neural networks that achieve arbitrarily small excess risk $\epsilon>0$.

$\ell_1$-regularized Neural Networks are Improperly Learnable in Polynomial Time

no code implementations13 Oct 2015 Yuchen Zhang, Jason D. Lee, Michael. I. Jordan

The sample complexity and the time complexity of the presented method are polynomial in the input dimension and in $(1/\epsilon,\log(1/\delta), F(k, L))$, where $F(k, L)$ is a function depending on $(k, L)$ and on the activation function, independent of the number of neurons.

Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds

no code implementations5 Feb 2015 Yuchen Zhang, Martin J. Wainwright, Michael. I. Jordan

We study the following generalized matrix rank estimation problem: given an $n \times n$ matrix and a constant $c \geq 0$, estimate the number of eigenvalues that are greater than $c$.

Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss

no code implementations1 Jan 2015 Yuchen Zhang, Lin Xiao

We consider distributed convex optimization problems originated from sample average approximation of stochastic optimization, or empirical risk minimization in machine learning.

Distributed Computing Distributed Optimization

Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization

no code implementations10 Sep 2014 Yuchen Zhang, Lin Xiao

We consider a generic convex optimization problem associated with regularized empirical risk minimization of linear predictors.

Optimality guarantees for distributed statistical estimation

no code implementations5 May 2014 John C. Duchi, Michael. I. Jordan, Martin J. Wainwright, Yuchen Zhang

Large data sets often require performing distributed statistical estimation, with a full data set split across multiple machines and limited communication between machines.

Buy one get one free: Distant annotation of Chinese tense, event type and modality

no code implementations LREC 2014 Nianwen Xue, Yuchen Zhang

We describe a {``}distant annotation{''} method where we mark up the semantic tense, event type, and modality of Chinese events via a word-aligned parallel corpus.

Machine Translation Word Alignment

Information-theoretic lower bounds for distributed statistical estimation with communication constraints

no code implementations NeurIPS 2013 Yuchen Zhang, John Duchi, Michael. I. Jordan, Martin J. Wainwright

We establish minimax risk lower bounds for distributed statistical estimation given a budget $B$ of the total number of bits that may be communicated.

General Classification

Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates

no code implementations22 May 2013 Yuchen Zhang, John C. Duchi, Martin J. Wainwright

We establish optimal convergence rates for a decomposition-based scalable approach to kernel ridge regression.

Communication-Efficient Algorithms for Statistical Optimization

no code implementations NeurIPS 2012 Yuchen Zhang, Martin J. Wainwright, John C. Duchi

The first algorithm is an averaging method that distributes the $N$ data samples evenly to $m$ machines, performs separate minimization on each subset, and then averages the estimates.

Learning-To-Rank

Comunication-Efficient Algorithms for Statistical Optimization

no code implementations19 Sep 2012 Yuchen Zhang, John C. Duchi, Martin Wainwright

We analyze two communication-efficient algorithms for distributed statistical optimization on large-scale data sets.

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