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Author Information
Suriya Gunasekar (TTI Chicago)
Jason Lee (University of Southern California)
Daniel Soudry (Technion)
I am an assistant professor in the Department of Electrical Engineering at the Technion, working in the areas of Machine learning and theoretical neuroscience. I am especially interested in all aspects of neural networks and deep learning. I did my post-doc (as a Gruss Lipper fellow) working with Prof. Liam Paninski in the Department of Statistics, the Center for Theoretical Neuroscience the Grossman Center for Statistics of the Mind, the Kavli Institute for Brain Science, and the NeuroTechnology Center at Columbia University. I did my Ph.D. (2008-2013, direct track) in the Network Biology Research Laboratory in the Department of Electrical Engineering at the Technion, Israel Institute of technology, under the guidance of Prof. Ron Meir. In 2008 I graduated summa cum laude with a B.Sc. in Electrical Engineering and a B.Sc. in Physics, after studying in the Technion since 2004.
Nati Srebro (TTI-Chicago)
More from the Same Authors
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2020 Poster: On Uniform Convergence and Low-Norm Interpolation Learning »
Lijia Zhou · Danica Sutherland · Nati Srebro -
2020 Poster: Reducing Adversarially Robust Learning to Non-Robust PAC Learning »
Omar Montasser · Steve Hanneke · Nati Srebro -
2020 Poster: Implicit Regularization and Convergence for Weight Normalization »
Xiaoxia Wu · Edgar Dobriban · Tongzheng Ren · Shanshan Wu · Zhiyuan Li · Suriya Gunasekar · Rachel Ward · Qiang Liu -
2020 Spotlight: On Uniform Convergence and Low-Norm Interpolation Learning »
Lijia Zhou · Danica Sutherland · Nati Srebro -
2020 Poster: Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy »
Edward Moroshko · Blake Woodworth · Suriya Gunasekar · Jason Lee · Nati Srebro · Daniel Soudry -
2020 Poster: Minibatch vs Local SGD for Heterogeneous Distributed Learning »
Blake Woodworth · Kumar Kshitij Patel · Nati Srebro -
2020 Spotlight: Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy »
Edward Moroshko · Blake Woodworth · Suriya Gunasekar · Jason Lee · Nati Srebro · Daniel Soudry -
2019 Poster: A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off »
Yaniv Blumenfeld · Dar Gilboa · Daniel Soudry -
2019 Poster: Post training 4-bit quantization of convolutional networks for rapid-deployment »
Ron Banner · Yury Nahshan · Daniel Soudry -
2018 Poster: Norm matters: efficient and accurate normalization schemes in deep networks »
Elad Hoffer · Ron Banner · Itay Golan · Daniel Soudry -
2018 Poster: Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization »
Blake Woodworth · Jialei Wang · Adam Smith · Brendan McMahan · Nati Srebro -
2018 Spotlight: Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization »
Blake Woodworth · Jialei Wang · Adam Smith · Brendan McMahan · Nati Srebro -
2018 Spotlight: Norm matters: efficient and accurate normalization schemes in deep networks »
Elad Hoffer · Ron Banner · Itay Golan · Daniel Soudry -
2018 Poster: Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced »
Simon Du · Wei Hu · Jason Lee -
2018 Poster: The Everlasting Database: Statistical Validity at a Fair Price »
Blake Woodworth · Vitaly Feldman · Saharon Rosset · Nati Srebro -
2018 Poster: Adding One Neuron Can Eliminate All Bad Local Minima »
SHIYU LIANG · Ruoyu Sun · Jason Lee · R. Srikant -
2018 Poster: On preserving non-discrimination when combining expert advice »
Avrim Blum · Suriya Gunasekar · Thodoris Lykouris · Nati Srebro -
2018 Poster: Provably Correct Automatic Sub-Differentiation for Qualified Programs »
Sham Kakade · Jason Lee -
2018 Poster: Scalable methods for 8-bit training of neural networks »
Ron Banner · Itay Hubara · Elad Hoffer · Daniel Soudry -
2018 Poster: On the Convergence and Robustness of Training GANs with Regularized Optimal Transport »
Maziar Sanjabi · Jimmy Ba · Meisam Razaviyayn · Jason Lee -
2017 Poster: Train longer, generalize better: closing the generalization gap in large batch training of neural networks »
Elad Hoffer · Itay Hubara · Daniel Soudry -
2017 Poster: The Marginal Value of Adaptive Gradient Methods in Machine Learning »
Ashia C Wilson · Becca Roelofs · Mitchell Stern · Nati Srebro · Benjamin Recht -
2017 Oral: The Marginal Value of Adaptive Gradient Methods in Machine Learning »
Ashia C Wilson · Becca Roelofs · Mitchell Stern · Nati Srebro · Benjamin Recht -
2017 Oral: Train longer, generalize better: closing the generalization gap in large batch training of neural networks »
Elad Hoffer · Itay Hubara · Daniel Soudry -
2017 Poster: Gradient Descent Can Take Exponential Time to Escape Saddle Points »
Simon Du · Chi Jin · Jason D Lee · Michael Jordan · Aarti Singh · Barnabas Poczos -
2017 Poster: Stochastic Approximation for Canonical Correlation Analysis »
Raman Arora · Teodor Vanislavov Marinov · Poorya Mianjy · Nati Srebro -
2017 Poster: Exploring Generalization in Deep Learning »
Behnam Neyshabur · Srinadh Bhojanapalli · David Mcallester · Nati Srebro -
2017 Poster: Implicit Regularization in Matrix Factorization »
Suriya Gunasekar · Blake Woodworth · Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro -
2017 Spotlight: Implicit Regularization in Matrix Factorization »
Suriya Gunasekar · Blake Woodworth · Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro -
2017 Spotlight: Gradient Descent Can Take Exponential Time to Escape Saddle Points »
Simon Du · Chi Jin · Jason D Lee · Michael Jordan · Aarti Singh · Barnabas Poczos -
2016 Poster: Preference Completion from Partial Rankings »
Suriya Gunasekar · Sanmi Koyejo · Joydeep Ghosh -
2016 Poster: Tight Complexity Bounds for Optimizing Composite Objectives »
Blake Woodworth · Nati Srebro -
2016 Poster: Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis »
Weiran Wang · Jialei Wang · Dan Garber · Dan Garber · Nati Srebro -
2016 Oral: Matrix Completion has No Spurious Local Minimum »
Rong Ge · Jason Lee · Tengyu Ma -
2016 Poster: Global Optimality of Local Search for Low Rank Matrix Recovery »
Srinadh Bhojanapalli · Behnam Neyshabur · Nati Srebro -
2016 Poster: Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations »
Behnam Neyshabur · Yuhuai Wu · Russ Salakhutdinov · Nati Srebro -
2016 Poster: Matrix Completion has No Spurious Local Minimum »
Rong Ge · Jason Lee · Tengyu Ma -
2016 Poster: Equality of Opportunity in Supervised Learning »
Moritz Hardt · Eric Price · Eric Price · Nati Srebro -
2016 Poster: Binarized Neural Networks »
Itay Hubara · Matthieu Courbariaux · Daniel Soudry · Ran El-Yaniv · Yoshua Bengio -
2016 Poster: Normalized Spectral Map Synchronization »
Yanyao Shen · Qixing Huang · Nati Srebro · Sujay Sanghavi -
2015 Poster: Unified View of Matrix Completion under General Structural Constraints »
Suriya Gunasekar · Arindam Banerjee · Joydeep Ghosh -
2015 Poster: Evaluating the statistical significance of biclusters »
Jason D Lee · Yuekai Sun · Jonathan E Taylor -
2015 Poster: Path-SGD: Path-Normalized Optimization in Deep Neural Networks »
Behnam Neyshabur · Russ Salakhutdinov · Nati Srebro -
2014 Poster: Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices »
Austin Benson · Jason D Lee · Bartek Rajwa · David F Gleich -
2014 Poster: Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm »
Deanna Needell · Rachel Ward · Nati Srebro -
2014 Spotlight: Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices »
Austin Benson · Jason D Lee · Bartek Rajwa · David F Gleich -
2014 Poster: Exact Post Model Selection Inference for Marginal Screening »
Jason D Lee · Jonathan E Taylor -
2014 Poster: Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights »
Daniel Soudry · Itay Hubara · Ron Meir -
2013 Workshop: Learning Faster From Easy Data »
Peter Grünwald · Wouter M Koolen · Sasha Rakhlin · Nati Srebro · Alekh Agarwal · Karthik Sridharan · Tim van Erven · Sebastien Bubeck -
2013 Workshop: Large Scale Matrix Analysis and Inference »
Reza Zadeh · Gunnar Carlsson · Michael Mahoney · Manfred K. Warmuth · Wouter M Koolen · Nati Srebro · Satyen Kale · Malik Magdon-Ismail · Ashish Goel · Matei A Zaharia · David Woodruff · Ioannis Koutis · Benjamin Recht -
2013 Poster: On model selection consistency of penalized M-estimators: a geometric theory »
Jason D Lee · Yuekai Sun · Jonathan E Taylor -
2013 Poster: Using multiple samples to learn mixture models »
Jason D Lee · Ran Gilad-Bachrach · Rich Caruana -
2013 Spotlight: Using multiple samples to learn mixture models »
Jason D Lee · Ran Gilad-Bachrach · Rich Caruana -
2013 Poster: Stochastic Optimization of PCA with Capped MSG »
Raman Arora · Andrew Cotter · Nati Srebro -
2013 Poster: Auditing: Active Learning with Outcome-Dependent Query Costs »
Sivan Sabato · Anand D Sarwate · Nati Srebro -
2013 Poster: The Power of Asymmetry in Binary Hashing »
Behnam Neyshabur · Nati Srebro · Russ Salakhutdinov · Yury Makarychev · Payman Yadollahpour -
2012 Poster: Proximal Newton-type Methods for Minimizing Convex Objective Functions in Composite Form »
Jason D Lee · Yuekai Sun · Michael Saunders -
2012 Poster: Sparse Prediction with the $k$-Support Norm »
Andreas Argyriou · Rina Foygel · Nati Srebro -
2012 Spotlight: Sparse Prediction with the $k$-Support Norm »
Andreas Argyriou · Rina Foygel · Nati Srebro -
2012 Poster: Matrix reconstruction with the local max norm »
Rina Foygel · Nati Srebro · Russ Salakhutdinov -
2011 Poster: Beating SGD: Learning SVMs in Sublinear Time »
Elad Hazan · Tomer Koren · Nati Srebro -
2011 Poster: Better Mini-Batch Algorithms via Accelerated Gradient Methods »
Andrew Cotter · Ohad Shamir · Nati Srebro · Karthik Sridharan -
2011 Poster: On the Universality of Online Mirror Descent »
Nati Srebro · Karthik Sridharan · Ambuj Tewari -
2011 Poster: Learning with the weighted trace-norm under arbitrary sampling distributions »
Rina Foygel · Russ Salakhutdinov · Ohad Shamir · Nati Srebro -
2010 Session: Spotlights Session 11 »
Nati Srebro -
2010 Session: Oral Session 13 »
Nati Srebro -
2010 Poster: Tight Sample Complexity of Large-Margin Learning »
Sivan Sabato · Nati Srebro · Naftali Tishby -
2010 Poster: Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm »
Russ Salakhutdinov · Nati Srebro -
2010 Poster: Practical Large-Scale Optimization for Max-norm Regularization »
Jason D Lee · Benjamin Recht · Russ Salakhutdinov · Nati Srebro · Joel A Tropp -
2010 Poster: Smoothness, Low Noise and Fast Rates »
Nati Srebro · Karthik Sridharan · Ambuj Tewari -
2009 Workshop: Understanding Multiple Kernel Learning Methods »
Brian McFee · Gert Lanckriet · Francis Bach · Nati Srebro -
2009 Poster: Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data »
Boaz Nadler · Nati Srebro · Xueyuan Zhou -
2009 Spotlight: Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data »
Boaz Nadler · Nati Srebro · Xueyuan Zhou -
2008 Poster: Fast Rates for Regularized Objectives »
Karthik Sridharan · Shai Shalev-Shwartz · Nati Srebro