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July 17, 2022 Expo schedule » New in ML »

Timezone: America/New_York »

Indicates the beginning of a session

 Tue Jul 19, 2022

Time Hall G
04:15 PM (Orals)
T: Learning/Deep Learning Theory
H-Consistency Bounds for Surrogate Loss Minimizers
04:35 PM (Spotlights)
Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent
04:40 PM (Spotlights)
The Teaching Dimension of Regularized Kernel Learners
04:45 PM (Spotlights)
Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation
04:50 PM (Spotlights)
TURF: Two-Factor, Universal, Robust, Fast Distribution Learning Algorithm
04:55 PM (Spotlights)
Multiclass learning with margin: exponential rates with no bias-variance trade-off
05:00 PM (Orals)
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models
05:20 PM (Spotlights)
High Probability Guarantees for Nonconvex Stochastic Gradient Descent with Heavy Tails
05:25 PM (Spotlights)
An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn
05:30 PM (Spotlights)
Inductive Biases and Variable Creation in Self-Attention Mechanisms
05:35 PM (Spotlights)
Topology-aware Generalization of Decentralized SGD
05:40 PM (Spotlights)
Understanding Gradient Descent on the Edge of Stability in Deep Learning