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Oral
Thu Jul 22 09:00 PM -- 09:20 PM (KST)
Tilting the playing field: Dynamical loss functions for machine learning
In Deep Learning Theory 6
Miguel Ruiz Garcia · Ge Zhang · Samuel Schoenholz · Andrea Liu
[ Paper ]
Spotlight
Thu Jul 22 09:20 PM -- 09:25 PM (KST)
Adversarial Robustness Guarantees for Random Deep Neural Networks
In Deep Learning Theory 6
Giacomo De Palma · Bobak T Kiani · Seth Lloyd
[ Paper ]
Spotlight
Thu Jul 22 09:25 PM -- 09:30 PM (KST)
Implicit Bias of Linear RNNs
In Deep Learning Theory 6
Melikasadat Emami · Mojtaba Sahraee-Ardakan · Parthe Pandit · Sundeep Rangan · Alyson Fletcher
[ Paper ]
Spotlight
Thu Jul 22 09:30 PM -- 09:35 PM (KST)
Analyzing the tree-layer structure of Deep Forests
In Deep Learning Theory 6
Ludovic Arnould · Claire Boyer · Erwan Scornet
[ Paper ]
Spotlight
Thu Jul 22 09:35 PM -- 09:40 PM (KST)
Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
In Deep Learning Theory 6
Eran Malach · Pritish Kamath · Emmanuel Abbe · Nati Srebro
[ Paper ]
Spotlight
Thu Jul 22 09:40 PM -- 09:45 PM (KST)
Implicit Regularization in Tensor Factorization
In Deep Learning Theory 6
Noam Razin · Asaf Maman · Nadav Cohen
[ Paper ]
Spotlight
Thu Jul 22 09:45 PM -- 09:50 PM (KST)
Uniform Convergence, Adversarial Spheres and a Simple Remedy
In Deep Learning Theory 6
Gregor Bachmann · Seyed Moosavi · Thomas Hofmann
[ Paper ]
Q&A
Thu Jul 22 09:50 PM -- 09:55 PM (KST)
Q&A
In Deep Learning Theory 6