55 Results

Poster
Tue 7:00 Self-Concordant Analysis of Frank-Wolfe Algorithms
Pavel Dvurechenskii, Petr Ostroukhov, Kamil Safin, Shimrit Shtern, Mathias Staudigl
Poster
Tue 7:00 FetchSGD: Communication-Efficient Federated Learning with Sketching
Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora
Poster
Tue 7:00 The Buckley-Osthus model and the block preferential attachment model: statistical analysis and application
Wenpin Tang, Xin Guo, Fengmin Tang
Poster
Tue 7:00 Faster Graph Embeddings via Coarsening
Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang
Poster
Tue 7:00 Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization
Richard Zhang, Daniel Golovin
Poster
Tue 7:00 Manifold Identification for Ultimately Communication-Efficient Distributed Optimization
Yu-Sheng Li, Wei-Lin Chiang, Ching-pei Lee
Poster
Tue 7:00 Streaming Submodular Maximization under a k-Set System Constraint
Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi
Poster
Tue 7:00 Stochastic Optimization for Non-convex Inf-Projection Problems
Yan Yan, Yi Xu, Lijun Zhang, Wang Xiaoyu, Tianbao Yang
Poster
Tue 7:00 Semismooth Newton Algorithm for Efficient Projections onto $\ell_{1, \infty}$-norm Ball
Dejun Chu, Changshui Zhang, Shiliang Sun, Qing Tao
Poster
Tue 7:00 Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner
Poster
Tue 8:00 Closing the convergence gap of SGD without replacement
Shashank Rajput, Anant Gupta, Dimitris Papailiopoulos
Poster
Tue 9:00 Nearly Linear Row Sampling Algorithm for Quantile Regression
Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
Poster
Tue 9:00 Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis
John Park, Kenneth Carr, Stephan Zheng, Yisong Yue, Rose Yu
Poster
Tue 9:00 Fast OSCAR and OWL Regression via Safe Screening Rules
Runxue Bao, Bin Gu, Heng Huang
Poster
Tue 11:00 Near-linear time Gaussian process optimization with adaptive batching and resparsification
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
Poster
Tue 12:00 Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization
GEOFFREY Negiar, Gideon Dresdner, Alicia Yi-Ting Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa
Poster
Tue 13:00 Optimal Randomized First-Order Methods for Least-Squares Problems
Jonathan Lacotte, Mert Pilanci
Poster
Tue 14:00 Training Neural Networks for and by Interpolation
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
Poster
Tue 14:00 Extreme Multi-label Classification from Aggregated Labels
Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit Dhillon
Poster
Tue 18:00 Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization
Pan Zhou, Xiao-Tong Yuan
Poster
Tue 18:00 Logistic Regression for Massive Data with Rare Events
HaiYing Wang
Poster
Wed 5:00 Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension
Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan, Roi Sinoff
Poster
Wed 5:00 Accelerating Large-Scale Inference with Anisotropic Vector Quantization
Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar
Poster
Wed 5:00 Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript
Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui
Poster
Wed 8:00 On Coresets for Regularized Regression
Rachit Chhaya, Supratim Shit, Anirban Dasgupta
Poster
Wed 8:00 Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification
Hui Ye, Zhiyu Chen, Da-Han Wang, Brian D Davison
Poster
Wed 8:00 The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phil Gibbons
Poster
Wed 8:00 Coresets for Clustering in Graphs of Bounded Treewidth
Daniel Baker, Vladimir Braverman, Lingxiao Huang, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu
Poster
Wed 8:00 Sets Clustering
Ibrahim Jubran, Murad Tukan, Alaa Maalouf, Dan Feldman
Poster
Wed 10:00 How to Solve Fair k-Center in Massive Data Models
Ashish Chiplunkar, Sagar Kale, Sivaramakrishnan Natarajan Ramamoorthy
Poster
Wed 10:00 Continuous-time Lower Bounds for Gradient-based Algorithms
Michael Muehlebach, Michael Jordan
Poster
Wed 10:00 AdaScale SGD: A User-Friendly Algorithm for Distributed Training
Tyler Johnson, Pulkit Agrawal, Haijie Gu, Carlos Guestrin
Poster
Wed 11:00 Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulié
Poster
Wed 12:00 Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition
Alex Gittens, Kareem Aggour, Bülent Yener
Poster
Wed 12:00 On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent
Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion
Poster
Wed 12:00 Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization
Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtarik
Poster
Wed 13:00 Growing Adaptive Multi-hyperplane Machines
Nemanja Djuric, Zhuang Wang, Slobodan Vucetic
Poster
Wed 14:00 Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems
Filip Hanzely, Dmitry Kovalev, Peter Richtarik
Poster
Wed 16:00 Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
Poster
Thu 6:00 Universal Asymptotic Optimality of Polyak Momentum
Damien Scieur, Fabian Pedregosa
Poster
Thu 6:00 Acceleration through spectral density estimation
Fabian Pedregosa, Damien Scieur
Poster
Thu 6:00 Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization
Deb Mahapatra, Vaibhav Rajan
Poster
Thu 6:00 On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
Darren Lin, Chi Jin, Michael Jordan
Poster
Thu 6:00 Almost Tune-Free Variance Reduction
Bingcong Li, Lingda Wang, Georgios B. Giannakis
Poster
Thu 6:00 Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex Programming
Daoli Zhu, Lei Zhao
Poster
Thu 7:00 Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence
Lijun Ding, Tom Fei, Qiantong Xu, Chengrun Yang
Poster
Thu 7:00 Simultaneous Inference for Massive Data: Distributed Bootstrap
Yang Yu, Shih-Kang Chao, Guang Cheng
Poster
Thu 8:00 One-shot Distributed Ridge Regression in High Dimensions
Yue Sheng, Edgar Dobriban
Poster
Thu 8:00 Coresets for Data-efficient Training of Machine Learning Models
Baharan Mirzasoleiman, Jeff Bilmes, Jure Leskovec
Poster
Thu 9:00 ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications
Kinjal Basu, Amol Ghoting, Rahul Mazumder, Yao Pan
Poster
Thu 9:00 The Implicit Regularization of Stochastic Gradient Flow for Least Squares
Alnur Ali, Edgar Dobriban, Ryan Tibshirani
Poster
Thu 12:00 Random extrapolation for primal-dual coordinate descent
Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
Poster
Thu 12:00 Composable Sketches for Functions of Frequencies: Beyond the Worst Case
Edith Cohen, Ofir Geri, Rasmus Pagh
Poster
Thu 12:00 Conditional gradient methods for stochastically constrained convex minimization
Maria Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher
Poster
Thu 13:00 Stochastic Subspace Cubic Newton Method
Filip Hanzely, Nikita Doikov, Yurii Nesterov, Peter Richtarik