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Poster
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"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach
lingyu gu · Yongqi Du · yuan zhang · Di Xie · Shiliang Pu · Robert Qiu · Zhenyu Liao
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Poster
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Thu 14:00
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D-GCCA: Decomposition-based Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data
Hai Shu · Zhe Qu · Hongtu Zhu
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Poster
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Information bottleneck theory of high-dimensional regression: relevancy, efficiency and optimality
Vudtiwat Ngampruetikorn · David Schwab
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Poster
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Thu 14:00
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DGD^2: A Linearly Convergent Distributed Algorithm For High-dimensional Statistical Recovery
Marie Maros · Gesualdo Scutari
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Poster
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Thu 9:00
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Learning Individualized Treatment Rules with Many Treatments: A Supervised Clustering Approach Using Adaptive Fusion
Haixu Ma · Donglin Zeng · Yufeng Liu
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Poster
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Thu 9:00
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Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions
Omri Ben-Eliezer · Dan Mikulincer · Ilias Zadik
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Poster
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Tue 14:00
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Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation
Kristian Georgiev · Samuel Hopkins
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Poster
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Thu 14:00
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A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Lijia Zhou · Frederic Koehler · Pragya Sur · Danica J. Sutherland · Nati Srebro
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Poster
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Tue 9:00
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Outlier-Robust Sparse Estimation via Non-Convex Optimization
Yu Cheng · Ilias Diakonikolas · Rong Ge · Shivam Gupta · Daniel Kane · Mahdi Soltanolkotabi
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Poster
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Thu 9:00
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High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Jimmy Ba · Murat Erdogdu · Taiji Suzuki · Zhichao Wang · Denny Wu · Greg Yang
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Workshop
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LSGANs with Gradient Regularizers are Smooth High-dimensional Interpolators
Siddarth Asokan · Chandra Seelamantula
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Poster
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Tue 14:00
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Multi-layer State Evolution Under Random Convolutional Design
Max Daniels · Cedric Gerbelot · Florent Krzakala · Lenka Zdeborová
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