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Papers

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2021 NIPS
2021 NIPS
Learning where to learn: Gradient sparsity in meta and continual learning
Johannes von Oswald, Dominic Zhao, Seijin Kobayashi et al.
2021 NIPS
Learning with Algorithmic Supervision via Continuous Relaxations
Felix Petersen, Christian Borgelt, Hilde Kuehne et al.
2021 NIPS
Learning with Holographic Reduced Representations
Ashwinkumar Ganesan, Hang Gao, Sunil Gandhi et al.
2021 NIPS
Learning with Labeling Induced Abstentions
Kareem Amin, Giulia DeSalvo, Afshin Rostamizadeh
2021 NIPS
Learning with Noisy Correspondence for Cross-modal Matching
Zhenyu Huang, Guocheng Niu, Xiao Liu et al.
2021 NIPS
Learning with User-Level Privacy
Daniel Levy, Ziteng Sun, Kareem Amin et al.
2021 NIPS
Least Square Calibration for Peer Reviews
Sijun Tan, Jibang Wu, Xiaohui Bei et al.
2021 NIPS
Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces
Kirill Struminsky, Artyom Gadetsky, Denis Rakitin et al.
2021 NIPS
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation
Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar et al.
2021 NIPS
Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering
Vincent Sitzmann, Semon Rezchikov, Bill Freeman et al.
2021 NIPS
2021 NIPS
2021 NIPS
2021 NIPS
List-Decodable Mean Estimation in Nearly-PCA Time
Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard et al.
2021 NIPS
2021 NIPS