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Poster
Tue 14:00 Alternating Direction Method of Multipliers for Quantization
Tianjian Huang · Prajwal Singhania · Maziar Sanjabi · Pabitra Mitra · Meisam Razaviyayn
Poster
Tue 14:00 Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences
Sreejith Sreekumar · Zhengxin Zhang · Ziv Goldfeld
Poster
Tue 14:00 Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization
Jelena Diakonikolas · Constantinos Daskalakis · Michael Jordan
Poster
Tue 14:00 Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning
Hitesh Sapkota · Yiming Ying · Feng Chen · Qi Yu
Poster
Tue 14:00 A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks
Zhiqi Bu · Shiyun Xu · Kan Chen
Poster
Tue 14:00 Accelerating Metropolis-Hastings with Lightweight Inference Compilation
Feynman Liang · Nimar Arora · Nazanin Tehrani · Yucen Li · Michael Tingley · Erik Meijer
Poster
Tue 18:30 Mirror Descent View for Neural Network Quantization
Thalaiyasingam Ajanthan · Kartik Gupta · Philip Torr · RICHARD HARTLEY · Puneet Dokania
Poster
Tue 18:30 Understanding the wiring evolution in differentiable neural architecture search
Sirui Xie · Shoukang Hu · Xinjiang Wang · Chunxiao Liu · Jianping Shi · Xunying Liu · Dahua Lin
Poster
Tue 18:30 Understanding Gradient Clipping In Incremental Gradient Methods
Jiang Qian · Yuren Wu · Bojin Zhuang · Shaojun Wang · Jing Xiao
Poster
Wed 6:00 Hyperparameter Transfer Learning with Adaptive Complexity
Samuel Horváth · Aaron Klein · Peter Richtarik · Cedric Archambeau
Poster
Wed 6:00 Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network
Tianyang Hu · Wenjia Wang · Cong Lin · Guang Cheng
Poster
Wed 6:00 On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions
Kai Brügge · Asja Fischer · Christian Igel