09:32

BayLearn 2024—01 Welcome to BayLearn 2024

47:12

BayLearn2024—02 Keynote1 Haghtalab

17:45

BayLearn2024—03 Oral1 Bazgir

45:59

BayLearn2024—04 AI Safety Panel

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BayLearn2024—05 Oral2 Zhou

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BayLearn2024—06 Oral3 Wu

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BayLearn2024—07 Keynote2 Anguelov

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BayLearn2024—08 Keynote3 Socher

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BayLearn2024—09 Oral4 Wu

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BayLearn2024—10 Oral5 Nie

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BayLearn2024—11 Oral6 Kashyap

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BayLearn2024—12 Oral7 Wei

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BayLearn 2023: Oral Presentations—Session 2

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BayLearn 2023: Oral Presentations—Session 1

41:35

BayLearn 2023: Niloufar Salehi

46:33

BayLearn 2023: Chris Re

59:29

BayLearn 2023: Percy Liang

01:00:30

BayLearn 2023: Fei Fei Li

14:05

BayLearn 2023: Welcome to BayLearn 2023

03:58

BayLearn 2021: Poster A-1: LocoProp: Enhancing BackProp via Local Loss Optimization

04:37

BayLearn 2021: Poster B-20: Decomposing Variance from Mini-Batch Order and Parameter Initialization

05:13

BayLearn 2021: Poster A-11: Accuracy on the Line

04:26

BayLearn 2021: Poster A-19: Interval Deep Learning

05:29

BayLearn 2021: Poster B-9: ML-CI: Machine Learning Confidence Intervals for Covid-19 forecasts

05:33

BayLearn 2021: Poster A-05: A Unified Approach to Ads Relevance with Multiple Relevance Objectives

06:03

BayLearn 2021: Poster A-06: Intrinsic Sliced Wasserstein Distances on Manifolds and Graphs

05:43

BayLearn 2021: Poster A-09: Evidential Softmax: A Sparse Multimodal Alternative to Softmax

04:54

BayLearn 2021: Poster A-04: Offline Reinforcement Learning for Mobile Notifications

04:47

BayLearn 2021:Poster A-3:A Near-Optimal Method for Minimizing the Maximum of N Convex Loss Functions

04:04

BayLearn 2021:Poster B-11:Distributed Full-batch Training of GNNs Using Sequential Rematerialization

05:01

BayLearn 2021: Poster B-02: What Can I Do Here? Learning New Skills by Imagining Visual Affordances

05:23

BayLearn 2021: Poster A-16: Finding Experts in Transformer Models

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BayLearn 2021: Poster B-13: Embeddings for Linking Adversarial Name Strings

05:03

BayLearn 2021: Poster B-07: SkillRank: Ranking Skills in Job Market

06:10

BayLearn 2021: Poster B-19: Revisiting Nearest Neighbors from a signal approximation perspective

04:17

BayLearn 2021: Poster A-13: Minimizing Communication while Maximizing Performance in Multi-Agent RL

04:37

BayLearn 2021: Poster B-15: Evolving Reinforcement Learning Algorithms

05:04

BayLearn 2021: Poster A-21: The Evolution of Out-of-Distribution RobustnessThroughout Fine-Tuning

04:53

BayLearn 2021: Poster B-03: Convolutional Networks Can Develop Blind Spots

04:57

BayLearn 2021: Poster B-01: Correspondence between neuroevolution and gradient descent

05:49

BayLearn 2021: Poster A-18: Coupled Gradient Estimators for Discrete Latent Variables

06:11

BayLearn 2021: Poster A-10: Deep Reinforcement Learning at the Edge of the Statistical Precipice

05:05

BayLearn 2021: Poster B-12: Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task..

04:47

BayLearn 2021: Poster A-07: Conditional Generation of Synthetic Geospatial Images

01:14

BayLearn 2021: Poster A-20: Loop Estimator for Discounted Values in Markov Reward Processes

05:09

BayLearn 2021: Poster A-12: Therapeutics Data Commons: ML Datasets & Tasks for Drug Discovery & Dev

04:03

BayLearn 2021: Poster B-04: Learning Rate Grafting: Transferability of Optimizer Tuning

04:56

BayLearn 2021: Poster B-6: Full Surround Monodepth from Multiple Cameras

07:42

BayLearn 2021: Poster B-16: Sparcle: Spatial Reassignment of spots to cells via maximum likelihood

04:55

BayLearn 2021: Poster A-02: Learning Period for Twitter Ads

05:58

BayLearn 2021: Poster B-21: Unsupervised Activity Segmentation by Joint Representation Learning

04:56

BayLearn 2021: Poster A-14: Is Pseudo-Lidar needed for Monocular 3D Object detection?

04:25

BayLearn 2021: Poster B-08: Soft Calibration Objectives for Neural Networks

05:57

BayLearn 2020: A DL Pipeline for Patient Diagnosis Prediction Using Electronic Health Records

05:17

BayLearn 2020: Adversarial Learning for Debiasing Knowledge Base Embeddings

04:53

BayLearn 2020: Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization

05:14

BayLearn 2020: Revisiting Spatial Invariance with Low-Rank Local Connectivity

04:57

BayLearn 2020: Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features

05:49

BayLearn 2020: What is being transferred in transfer learning?

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BayLearn 2020: Distributed Sketching Methods for Privacy Preserving Regression