Channel - Rising Stars in AI Symposium 2022 at KAUST
Rising Stars in AI Symposium 2022
The Rising Stars in AI Symposium is geared towards young researchers (including PhD students, PostDocs, young faculty) who have recently published promising work at leading venues. There will be tens of brief presentations about papers recently accepted at major AI conferences such as NeurIPS, CVPR, EMNLP, ACL, ICML, ICLR.
6/1/2022 7:33:54 AM
Channel Videos
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression
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3/15/2022 10:40:00 AM
Challenges in Real-world Applications of Neural Networks
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3/13/2022 12:40:00 PM
Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity
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3/13/2022 8:00:00 AM
Fast Weight Architectures for Language Modeling and Associative Inference
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3/14/2022 12:00:00 PM
FedNL: Making Newton-Type Methods Applicable to Federated Learning
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3/14/2022 10:30:00 AM
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
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3/15/2022 8:20:00 AM
FL_PyTorch: optimization research simulator for federated learning
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3/13/2022 6:20:00 AM
Information theoretic concepts for the perception and creation of music
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3/15/2022 12:40:00 PM
MAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions
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3/15/2022 8:40:00 AM
Overview of the methods for chemical reaction prediction
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3/13/2022 11:00:00 AM
Parameter-based Value Functions
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3/14/2022 10:40:00 AM
Principles of Compositionality Improve Systematic Generalization of Neural Networks
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3/14/2022 11:00:00 AM
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
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3/15/2022 12:15:00 PM
Shifted Compression Framework for Distributed Learning
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3/15/2022 6:40:00 PM
Towards interpretable and disentangled GANs
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3/13/2022 6:40:00 AM
Training a Weight Matrix to Train/Modify/Adapt Itself
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3/14/2022 12:20:00 PM
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