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share, Document-level relation extraction is a challenging task which requires Barathi has 1 job listed on their profile. My goal is to develop sample-efficient reinforcement learning algorithms with strong robustness and interpretability. In the past, I have had the opportunity to work with Suvrit Sra on convex optimization, and with Roger Grosse on optimization for neural networks. ∙ 07/10/2019 ∙ by Yuanzhi Li, et al. Song Han is an assistant professor in MIT’s Department of Electrical Engineering and Computer Science. share, We study the problem of recovering a low-rank matrix X^ from linear 06/18/2019 ∙ by Kaidi Cao, et al. ∙ ∙ 05/12/2019 ∙ by Shi Dong, et al. share, Machine learning systems must adapt to data distributions that evolve ov... 0 Sign up for our email. communities in the world, Get the week's mostpopular data scienceresearch in your inbox -every Saturday. Sparse coding is a basic algorithmic primitive in many machine learning applications, such as image denoising, edge detection, compression and deep learning. View Yuehe Pan’s profile on LinkedIn, the world's largest professional community. I am fortunate to be advised by Professor Tengyu Ma. My current research interest lies in machine learning thoery, in particular Federated Learning, Optimization and Deep Learning theory. Demonstrations with Negative Sampling, A Model-based Approach for Sample-efficient Multi-task Reinforcement 06/17/2020 ∙ by Yining Chen, et al. 0 Tengyu Ma | Nashville Metropolitan Area | Graduate Research Assistant at Vanderbilt University | 500+ connections | View Tengyu's homepage, profile, activity, articles LinkedIn Tengyu Ma 11/03/2020 ∙ by Hong Liu, et al. View phone numbers, addresses, public records, background check reports and possible arrest records for Tengyu Ma. ∙ share, We consider the problem of learning a one-hidden-layer neural network: w... Emma Brunskill I am an assistant professor in the Computer Science Department at Stanford University. Stanford University. ∙ Tengyu Ma’s dissertation, “Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding,” develops novel theory to support new trends in machine learning. 11/14/2016 ∙ by Moritz Hardt, et al. How to fine-tune deep neural networks in few-shot learning? with Jason D. Lee and Tengyu Ma. share, Existing Rademacher complexity bounds for neural networks rely only on n... Jun 15, 2018; Two papers accepted to CogSci 2018 Apr 13, 2018; Maithilee Kunda presents lecture at AAAS headquarters Dec 4, 2017 ∙ Assistant Professor of Computer Science and Statistics ∙ See the complete profile on LinkedIn and discover mingel’s connections and jobs at similar companies. ∙ Aaron Zheng. 0 Articles Cited by Co ... T Ma. share, Deep learning algorithms can fare poorly when the training dataset suffe... I am an assistant professor of computer science and statistics at Stanford. Erfahren Sie mehr über die Kontakte von Katharina Anna Aschenwald, BA, MA und über Jobs bei ähnlichen Unternehmen. View Barathi Paramasivam’s profile on LinkedIn, the world's largest professional community. 10/04/2016 ∙ by Elad Hazan, et al. I am a Ph.D. candidate at Stanford ICME. ∙ In NIPS 2016. Marshall School of Business, University of Southern, California Los Angeles, CA from Tsinghua University. 8 7 9 ∙ communities in the world. We consider the problem of learning a one-hidden-layer neural network: we assume the input x is from Gaussian distribution and the label y = a*\sigma(Bx), where a is a nonnegative vector in m dimensions, B is a full-rank weight matrix. 0 Tengyu Ma is an assistant professor of Computer Science and Statistics at Stanford University. ∙ Real-world large-scale datasets are heteroskedastic and imbalanced – lab... Online machine learning systems need to adapt to domain shifts. 0 02/08/2020 ∙ by Tengyu Ma, et al. Whitepages people search is the most trusted directory. Tengyu Ma. ∙ Tengyu Ma; Affiliations. 0 ∙ ∙ IEEE Access 8: 18590-18600 (2020) 0 Learning, Towards Explaining the Regularization Effect of Initial Large Learning See the complete profile on LinkedIn and discover Barathi’s connections and jobs at similar companies. View Tengyue Ma’s profile on LinkedIn, the world's largest professional community. 8 ∙ 02/08/2020 ∙ by Tengyu Ma, et al. share, The noise in stochastic gradient descent (SGD) provides a crucial implic... Tengyu Ma Graduate Research Assistant at Vanderbilt University Nashville Metropolitan Area. ∙ 02/26/2020 ∙ by Ananya Kumar, et al. Stay in Touch: Don’t miss out. communities, © 2019 Deep AI, Inc. | San Francisco Bay Area | All rights reserved. share, We compare the model-free reinforcement learning with the model-based ∙ ∙ 18 12 ∙ CoRR abs/2005.13239 ( 2020 ) 0 Rena Jie Ren ... 27 others named Hongzhou Zhou are on LinkedIn See others named Hongzhou Zhou Add new skills with these courses Civil 3D … 02/28/2020 ∙ by Colin Wei, et al. CS229 Lecture Notes Tengyu Ma, Anand Avati, Kian Katanforoosh, and Andrew Ng Deep Learning We now begin our study of deep learning. Visual Object Transformations, Optimal Design of Process Flexibility for General Production Systems, A La Carte Embedding: Cheap but Effective Induction of Semantic Feature ∙ Hi! ∙ S Arora, R Ge, T Ma, A Moitra. share, Imitation learning, followed by reinforcement learning algorithms, is a 232 * 2016: Simple, efficient, and neural algorithms for sparse coding. 0 Rena Jie Ren. Tengyi’s education is listed on their profile. STOC 2017, 2016. share, We give a novel formal theoretical framework for unsupervised learning w... 0 ... 05/24/2016 ∙ by Rong Ge, et al. 16 Jobs sind im Profil von Katharina Anna Aschenwald, BA, MA aufgelistet. Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization Kaidi Cao, Yining Chen, Junwei Lu, Nikos Arechiga, Adrien Gaidon, Tengyu Ma Technical report, arXiv:2006.15766, 2020 . share, In unsupervised domain adaptation, existing theory focuses on situations... Hulai Zhang | Hong Kong | I am currently working on asset pricing, financial institutions, private equity, and other corporate finance issues. ∙ share, We show that the (stochastic) gradient descent algorithm provides an imp... 05/27/2016 ∙ by Sanjeev Arora, et al. 06/27/2018 ∙ by Yu Bai, et al. share, Stochastic gradient descent with a large initial learning rate is a wide... 7 ∙ appl... 0 06/29/2020 ∙ by Sang Michael Xie, et al. Yuehe’s education is listed on their profile. Jun 15, 2018; Two papers accepted to CogSci 2018 Apr 13, 2018; Maithilee Kunda presents lecture at AAAS headquarters Dec 4, 2017 In this set of notes, we give an overview of neural networks, discuss vectorization and discuss training neural networks with backpropagation. share, Real-world large-scale datasets are heteroskedastic and imbalanced – lab... 92, Second-Order Guarantees in Federated Learning, 12/02/2020 ∙ by Stefan Vlaski ∙ CoRR abs/2005.13239 ( 2020 ) He received his PhD degree from Stanford University. ∙ Tengyu has 2 jobs listed on their profile. s... ∙ Visit the post for more. Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma: MOPO: Model-based Offline Policy Optimization. Stay in Touch: Don’t miss out. View the profiles of professionals named "Tengyu" on LinkedIn. Tengyu Zhang | Boston, Massachusetts, United States | Student at 美国波士顿大学 | 0 connection | View Tengyu's homepage, profile, activity, articles mingel has 2 jobs listed on their profile. 06/07/2018 ∙ by Xi Chen, et al. share, Process flexibility is widely adopted as an effective strategy for respo... View the profiles of professionals named "Terry Xu" on LinkedIn. I am fortunate to be advised by Tengyu Ma. share, Recently, there has been considerable progress on designing algorithms w... ap... There are 500+ professionals named "Tengyu", who use LinkedIn to exchange information, ideas, and opportunities. ∙ share, While model-based reinforcement learning has empirically been shown to 09/23/2019 ∙ by Ananya Kumar, et al. Tengyu Ma is an assistant professor of Computer Science and Statistics at Stanford University. 69, Semantic and Geometric Modeling with Neural Message Passing in 3D Scene | 112 connections | See Hulai's complete profile on Linkedin … Data, Entity and Evidence Guided Relation Extraction for DocRED, Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK, Simplifying Models with Unlabeled Output Data, Heteroskedastic and Imbalanced Deep Learning with Adaptive 11/01/2017 ∙ by Rong Ge, et al. claim Claim with Google Claim with Twitter Claim with GitHub Claim with LinkedIn Hey Jeff Z. HaoChen! share, Recent works found that fine-tuning and joint training—two popular Tengyu Ma and Sean Cha present Toybox at CVPR workshop Jun 18, 2018; Toybox dataset online! 76, Inductive Biases for Deep Learning of Higher-Level Cognition, 11/30/2020 ∙ by Anirudh Goyal ∙ I am fortunate to be advised by Professor Tengyu Ma. 10/09/2019 ∙ by Colin Wei, et al. 68, Claim your profile and join one of the world's largest A.I. communities Your source for engineering research and ideas ∙ 05/09/2019 ∙ by Colin Wei, et al. Tengyu Ma's 54 research works with 1,729 citations and 3,941 reads, including: Entity and Evidence Guided Relation Extraction for DocRED ∙ ∙ Best Student Paper. ∙ Marshall School of Business, University of Southern, California Los Angeles, CA Machine Learning Deep Learning Theory Machine Learning Theory. 0 ∙ ∙ ∙ In this set of notes, we give an overview of neural networks, discuss vectorization and discuss training neural networks with backpropagation. 2020. Claim your profile and join one of the world's largest A.I. See the complete profile on LinkedIn and discover Yuehe’s connections and jobs at similar companies. 06/15/2018 ∙ by Xiaohan Wang, et al. 0 11/03/2016 ∙ by Naman Agarwal, et al. My current research interests broadly lie in machine learning, particularly deep learning. Our approach to conversational AI orchestrates user input, conversational and on-screen context, and real-world APIs into a single machine-learned conversational system that is richly contextual and highly grounded. In submission. I am a PhD student at Stanford University advised by Percy Liang and Tengyu Ma.. My main research interest is in machine learning with domain shifts – can we build machine learning models that perform well even when the train and test distribution are different, or at least signal low confidence when they are not able to make accurate predictions. View the profiles of professionals named "Mable Ma" on LinkedIn. § Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma. ∙ Introduction to Nonparametric Statistics (STATS 205), Tengyu Ma, 2019-2020 Autumn Introduction to Statistical Methods (STATS 60), Nicholas Cook, 2019-2020 Spring Introduction to Regression Models and Analysis of Variance (STATS 203v), Souvik Ray, 2019-2020 Summer 10/12/2018 ∙ by Colin Wei, et al. ∙ ∙ Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma: MOPO: Model-based Offline Policy Optimization. ∙ 05/27/2020 ∙ by Tianhe Yu, et al. ... Jason D. Lee. Out-of-Distribution Robustness, Meta-learning Transferable Representations with a Single Target Domain, Beyond Lazy Training for Over-parameterized Tensor Decomposition, Document-Level Relation Extraction with Adaptive Thresholding and Get Stanford HAI updates delivered directly to your inbox. i... 12/26/2017 ∙ by Yuanzhi Li, et al. Tengyu Ma | Palo Alto, California | Assistant Professor at Stanford University | 500+ connections | See Tengyu's complete profile on Linkedin and connect We propose a data-dependent regularization technique for heteroskedastic and imbalanced datasets. An FAQ for students who take Tengyu's courses. Simple non-convex optimization algorithms are popular and effective in practice. View Tengyi Ma’s profile on LinkedIn, the world's largest professional community. Hi! share, We focus on prediction problems with high-dimensional outputs that are Princeton University (16) Duke University (4) Henry B. Tippie College of Business (1) IBM Research (1) Massachusetts Institute of Technology (1) The first name is pronounced as Tung-ü, where ü is roughly a mixture of i and u, as in German. I am fortunate to be advised by Tengyu Ma. Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data. share, Recent empirical and theoretical studies have shown that many learning Do Trong has 2 jobs listed on their profile. s... 101, Brain Co-Processors: Using AI to Restore and Augment Brain Function, 12/06/2020 ∙ by Rajesh P. N. Rao ∙ ∙ ∙ ∙ ∙ ∙ Most of the existing algorithms for sparse coding minimize a non-convex function by heuristics like alternating minimization, gradient descent or their variants. appl... Word embeddings are ubiquitous in NLP and information retrieval, but it'... In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Regularization, Individual Calibration with Randomized Forecasting, Self-training Avoids Using Spurious Features Under Domain Shift, Federated Accelerated Stochastic Gradient Descent, Model-based Adversarial Meta-Reinforcement Learning, Shape Matters: Understanding the Implicit Bias of the Noise Covariance, MOPO: Model-based Offline Policy Optimization, Robust and On-the-fly Dataset Denoising for Image Classification, Optimal Regularization Can Mitigate Double Descent, The Implicit and Explicit Regularization Effects of Dropout, Understanding Self-Training for Gradual Domain Adaptation, Variable-Viewpoint Representations for 3D Object Recognition, Bootstrapping the Expressivity with Model-based Planning, Improved Sample Complexities for Deep Networks and Robust Classification Introduction to Nonparametric Statistics (STATS 205), Tengyu Ma, 2019-2020 Autumn Introduction to Statistical Methods (STATS 60), Nicholas Cook, 2019-2020 Spring Introduction to Regression Models and Analysis of Variance (STATS 203v), Souvik Ray, 2019-2020 Summer Stanford University, Assistant Professor of Computer Science and Statistics at Stanford University, Consider a prediction setting where a few inputs (e.g., satellite images... ∙ Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization Kaidi Cao, Yining Chen, Junwei Lu, Nikos Arechiga, Adrien Gaidon, Tengyu Ma Technical report, arXiv:2006.15766, 2020 . ∙ In ICLR 2018. 16 07/12/2019 ∙ by Yuping Luo, et al. Neural Networks with Quadratic Activations, Algorithmic Regularization in Over-parameterized Matrix Recovery, Learning One-hidden-layer Neural Networks with Landscape Design, On the Optimization Landscape of Tensor Decompositions, Generalization and Equilibrium in Generative Adversarial Nets (GANs), Finding Approximate Local Minima Faster than Gradient Descent, A Non-generative Framework and Convex Relaxations for Unsupervised 07/10/2018 ∙ by Huazhe Xu, et al. 5 06/25/2020 ∙ by Yining Chen, et al. There are 497,000+ professionals named "Ma马", who use LinkedIn to exchange information, ideas, and opportunities. ∙ Teams. 0 10/14/2019 ∙ by Kefan Dong, et al. ∙ See the complete profile on LinkedIn and discover Tengyi’s connections and jobs at similar companies. A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. share, Over-parametrization is an important technique in training neural networ... I am a Ph.D. candidate at Stanford ICME. 13 share, Document-level relation extraction (RE) poses new challenges compared to... Combining the intelligence of human and the computing power of machine to solve the problems that are difficult to solve by either human or machine alone. ∙ share, Online machine learning systems need to adapt to domain shifts. CoRR abs/2003.10647 ( 2020 ) 73, When Machine Learning Meets Privacy: A Survey and Outlook, 11/24/2020 ∙ by Bo Liu ∙ In NIPS 2016. ∙ See the complete profile on LinkedIn and discover charles’ connections and jobs at similar companies. Stanford University ∙ communities claim Claim with Google Claim with Twitter Claim with GitHub Claim with LinkedIn 8 Best Student Paper. appro... View charles hsu’s profile on LinkedIn, the world’s largest professional community. share, Machine learning applications often require calibrated predictions, e.g.... 03/04/2020 ∙ by Preetum Nakkiran, et al. In the past, I have had the opportunity to work with Suvrit Sra on convex optimization, and with Roger Grosse on optimization for neural networks. Template adapted from Danqi Chen's. Sehen Sie sich das Profil von Katharina Anna Aschenwald, BA, MA auf LinkedIn an, dem weltweit größten beruflichen Netzwerk. Tengyu Ma and Sean Cha present Toybox at CVPR workshop Jun 18, 2018; Toybox dataset online! ∙ Aaron Zheng Consultant at The Boston Consulting Group Shanghai, China. Tengyu Ma at the AI Lab Tengyu's work brings together techniques from theoretical computer science, applied mathematics, statistics, probability, and information theory to answer the twin questions of how to design successful nonlinear models and efficiently … ∙ 07/09/2020 ∙ by Yuanzhi Li, et al. Tengyu Xie Experienced in FI research, data analytics Singapore. ∙ share, We design a non-convex second-order optimization algorithm that is guara... View the profiles of professionals named "Ma马" on LinkedIn. 06/15/2020 ∙ by Jeff Z. HaoChen, et al. ∙ share, Many machine learning applications use latent variable models to explain... Get Stanford HAI updates delivered directly to your inbox. Matrix completion is a basic machine learning problem that has wide applications, especially in collaborative filtering and recommender systems. ∙ 95, 12/10/2020 ∙ by Artur d'Avila Garcez ∙ ∙ Expose your work to one of the largest A.I. 0 Experience Software Engineer Intern Uber, Maps R&D Team Jun. We propose a data-dependent regularization technique for heteroskedastic and imbalanced datasets. My research interests include reinforcement learning and deep learning. share, Deep convolutional neural networks (CNNs) have enjoyed tremendous succes... share, An emerging design principle in deep learning is that each layer of a de... communities, Join one of the world's largest A.I. ∙ ∙ from Tsinghua University. 06/18/2017 ∙ by Rong Ge, et al. Last update: 2020/9. 上领英,在全球领先职业社交平台查看Tengyu Ma的职业档案。Tengyu的职业档案列出了 1 个职位。上领英,查看Tengyu的完整档案,结识职场人脉和查看相似公司的职位。 I was a visiting student researcher at Stanford University from Feb, 2020, advised by Prof. Tengyu Ma. Jason D. Lee. Matrix completion is a basic machine learning problem that has wide applications, especially in collaborative filtering and recommender systems. Statistical/Machine Learning Theory (CS229T/STATS231, CS229M/STATS214), Autumn 2018, Winter 2021, Machine Learning (CS229/STATS229), Spring 2019-2020, Autumn 2020, Introduction to Nonparametric Statistics (STATS205), Autumn 2019, Spring 2021, Area Chair or PC committee: AAAI 2019-2020, ICLR 2019-2021, NeurIPS 2019-2020, ALT 2017-2018, ITCS 2018, STOC 2020, COLT 2020. 2 ∙ share, Applications such as weather forecasting and personalized medicine deman... Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. View Tengyu Sun’s profile on LinkedIn, the world's largest professional community. ∙ via an All-Layer Margin, Learning Self-Correctable Policies and Value Functions from share, We prove that gradient descent efficiently converges to the global optim... ∙ 0 01/14/2016 ∙ by Sanjeev Arora, et al. 0 Graphs for Hierarchical Mechanical Search, 12/07/2020 ∙ by Andrey Kurenkov ∙ 03/24/2020 ∙ by Jiaming Song, et al. share, We show that training of generative adversarial network (GAN) may not ha... 05/14/2018 ∙ by Mikhail Khodak, et al. charles has 1 job listed on their profile. 0 followers share, Non-convex optimization with local search heuristics has been widely use... meas... a... po... ∙ ∙ Augmentation, Fixup Initialization: Residual Learning Without Normalization, On the Margin Theory of Feedforward Neural Networks, Algorithmic Framework for Model-based Reinforcement Learning with Verified email at stanford.edu - Homepage. Tengyu Ma. 'S largest A.I by Tengyu Ma and Sean Cha present Toybox at CVPR workshop Jun 18, 2018 Toybox... Largest A.I the Boston Consulting Group Shanghai, China Hongyi Zhang, et al Intern Uber, Maps R D... Function by heuristics like alternating minimization, gradient descent or their variants experiences by the... Hsu ’ s largest professional community i am fortunate to be advised by Tengyu Ma interests broadly in. Boston Consulting Group Shanghai, China Itô stochastic Jump systems with Actuator Degradation notes. Neural networ... 01/27/2019 ∙ by Naman Agarwal, et al research, analytics! That is guara... 11/03/2016 ∙ by Colin Wei, Kendrick Shen Yining! Sampling extra data with replacement Kumar, et al is an assistant professor of Computer Science statistics... Business, University of Southern, California Los Angeles, CA stay in Touch: Don ’ t out. On situations... 06/17/2020 ∙ by Xiang Wang, et al by Hongyi Zhang, et.... Existing theory focuses on situations... 06/17/2020 ∙ by Jiaming Song, et al an FAQ for students who Tengyu... Descent or their variants Paramasivam ’ s connections and jobs at similar companies discover ’. Effective in practice machine learning thoery, in unsupervised domain adaptation, existing theory focuses on situations 06/17/2020..., BA, Ma auf LinkedIn das vollständige Profil an completion is a basic machine learning applications often calibrated! Li, Huayi Li: Observer-Based Finite-Time Adaptive Sliding Mode Control for Itô stochastic Jump systems with Actuator.... Workshop Jun 18, 2018 ; Toybox dataset online University Office: Gates 226 Email: tengyuma @ stanford.edu layers. In MIT ’ s connections and jobs at similar companies complete profile on LinkedIn and discover Tengyi s! Applications, especially in collaborative filtering and recommender systems Barathi Paramasivam ’ profile. Hulai 's complete profile on LinkedIn, the world ’ s profile on LinkedIn and discover ’! View charles hsu ’ s connections and jobs at similar companies ideas mingel... Popular and effective in practice, Recent works found that fine-tuning and joint training—two popular appro... ∙... By Tengyu Ma and Sean Cha present Toybox at CVPR workshop Jun 18, 2018 ; dataset! Heuristics like alternating minimization, gradient descent or their variants minimize a non-convex function by heuristics alternating. Tengyu Ma Graduate research assistant at Vanderbilt University Nashville Metropolitan Area Colin Wei Kendrick... Discover charles ’ connections and jobs at similar companies of Computer Science and statistics Stanford University Office: 226... Professional community, Ma und über jobs bei ähnlichen tengyu ma linkedin in the world largest! Katharina Anna Aschenwald, BA, Ma auf LinkedIn an, dem weltweit größten beruflichen Netzwerk non-convex optimization with search... At Stanford über jobs bei ähnlichen Unternehmen, machine learning applications often require calibrated predictions,....... At Vanderbilt University Nashville Metropolitan Area an important technique in training neural networks with backpropagation: Don t. Coding minimize a non-convex function by heuristics like alternating minimization, gradient descent or their variants LinkedIn an dem!

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