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Oral
Fri Jun 14 01:00 AM -- 01:20 AM (KST) @ Room 104
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning
In Non-convex Optimization
Dong Yin · Yudong Chen · Kannan Ramchandran · Peter Bartlett
[ Oral] 
Oral
Fri Jun 14 01:20 AM -- 01:25 AM (KST) @ Room 104
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization
In Non-convex Optimization
Baojian Zhou · Feng Chen · Yiming Ying
[ Slides]  [ Oral] 
Oral
Fri Jun 14 01:25 AM -- 01:30 AM (KST) @ Room 104
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically
In Non-convex Optimization
Grant Rotskoff · Samy Jelassi · Joan Bruna · Eric Vanden-Eijnden
[ Slides]  [ Oral] 
Oral
Fri Jun 14 01:30 AM -- 01:35 AM (KST) @ Room 104
Width Provably Matters in Optimization for Deep Linear Neural Networks
In Non-convex Optimization
Simon Du · Wei Hu
[ Slides]  [ Oral] 
Oral
Fri Jun 14 01:35 AM -- 01:40 AM (KST) @ Room 104
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?
In Non-convex Optimization
Samet Oymak · Mahdi Soltanolkotabi
[ Slides]  [ Oral] 
Oral
Fri Jun 14 01:40 AM -- 02:00 AM (KST) @ Room 104
Power k-Means Clustering
In Non-convex Optimization
Jason Xu · Kenneth Lange
[ Slides]  [ Oral] 
Oral
Fri Jun 14 02:00 AM -- 02:05 AM (KST) @ Room 104
Distributed Learning over Unreliable Networks
In Non-convex Optimization
Chen Yu · Hanlin Tang · Cedric Renggli · Simon Kassing · Ankit Singla · Dan Alistarh · Ce Zhang · Ji Liu
[ Slides]  [ Oral] 
Oral
Fri Jun 14 02:05 AM -- 02:10 AM (KST) @ Room 104
Escaping Saddle Points with Adaptive Gradient Methods
In Non-convex Optimization
Matthew Staib · Sashank Jakkam Reddi · Satyen Kale · Sanjiv Kumar · Suvrit Sra
[ Slides]  [ Oral] 
Oral
Fri Jun 14 02:10 AM -- 02:15 AM (KST) @ Room 104
$\texttt{DoubleSqueeze}$: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression
In Non-convex Optimization
Hanlin Tang · Chen Yu · Xiangru Lian · Tong Zhang · Ji Liu
[ Slides]  [ Oral] 
Oral
Fri Jun 14 02:15 AM -- 02:20 AM (KST) @ Room 104
Model Function Based Conditional Gradient Method with Armijo-like Line Search
In Non-convex Optimization
Peter Ochs · Yura Malitsky
[ Slides]  [ Oral]