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The 2021 schedule is still incomplete
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Oral
Wed Jul 21 07:00 PM -- 07:20 PM (PDT)
Analysis of stochastic Lanczos quadrature for spectrum approximation
In Learning Theory 13
Tyler Chen · Thomas Trogdon · Shashanka Ubaru
[ Paper ]
Spotlight
Wed Jul 21 07:20 PM -- 07:25 PM (PDT)
Sample-Optimal PAC Learning of Halfspaces with Malicious Noise
In Learning Theory 13
Jie Shen
[ Paper ]
Spotlight
Wed Jul 21 07:25 PM -- 07:30 PM (PDT)
On Robust Mean Estimation under Coordinate-level Corruption
In Learning Theory 13
Zifan Liu · Jong Ho Park · Theo Rekatsinas · Christos Tzamos
[ Paper ]
Spotlight
Wed Jul 21 07:30 PM -- 07:35 PM (PDT)
Multidimensional Scaling: Approximation and Complexity
In Learning Theory 13
Erik Demaine · Adam C Hesterberg · Frederic Koehler · Jayson Lynch · John C Urschel
[ Paper ]
Spotlight
Wed Jul 21 07:35 PM -- 07:40 PM (PDT)
Toward Better Generalization Bounds with Locally Elastic Stability
In Learning Theory 13
Zhun Deng · Hangfeng He · Weijie Su
[ Paper ]
Spotlight
Wed Jul 21 07:40 PM -- 07:45 PM (PDT)
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
In Learning Theory 13
Jonathan Lacotte · Yifei Wang · Mert Pilanci
[ Paper ]
Spotlight
Wed Jul 21 07:45 PM -- 07:50 PM (PDT)
Interpreting and Disentangling Feature Components of Various Complexity from DNNs
In Learning Theory 13
Jie Ren · Mingjie Li · Zexu Liu · Quanshi Zhang
[ Paper ]
Q&A
Wed Jul 21 07:50 PM -- 07:55 PM (PDT)
Q&A
In Learning Theory 13