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Mon 17:00 Learning A Minimax Optimizer: A Pilot Study
Jiayi Shen · Xiaohan Chen · Howard Heaton · Tianlong Chen · Jialin Liu · Wotao Yin · Zhangyang Wang
Thu 9:00 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang · Yulia Tsvetkov · Orhan Firat · Yuan Cao
Tue 17:00 Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
Jeremy Cohen · Simran Kaur · Yuanzhi Li · Zico Kolter · Ameet Talwalkar
Mon 17:00 The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers
Preetum Nakkiran · Behnam Neyshabur · Hanie Sedghi
Tue 1:00 Learning the Pareto Front with Hypernetworks
Aviv Navon · Aviv Shamsian · Ethan Fetaya · Gal Chechik
Wed 9:00 Geometry-Aware Gradient Algorithms for Neural Architecture Search
Liam Li · Mikhail Khodak · Nina Balcan · Ameet Talwalkar
Thu 1:00 A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima
Zeke Xie · Issei Sato · Masashi Sugiyama
Thu 17:00 Convex Regularization behind Neural Reconstruction
Arda Sahiner · Morteza Mardani · Batu Ozturkler · Mert Pilanci · John M Pauly
Tue 9:00 FairBatch: Batch Selection for Model Fairness
Yuji Roh · Kangwook Lee · Steven Whang · Changho Suh
Tue 17:00 The Importance of Pessimism in Fixed-Dataset Policy Optimization
Jacob Buckman · Carles Gelada · Marc G Bellemare
Thu 1:00 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell · Insu Han · Elvis Dohmatob · Jennifer Gillenwater · Victor-Emmanuel Brunel
Mon 1:00 Wasserstein-2 Generative Networks
Alexander Korotin · Vage Egiazarian · Arip Asadulaev · Alexander Safin · Evgeny Burnaev