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Learning Attractor Dynamics for Generative Memory
Yan Wu, Gregory Wayne, Karol Gregor, Timothy Lillicrap
These mechanisms typically retrieve items in a single step and are fixed after training.
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models Andy Zhou
One of the goals of machine learning is to develop systems that can generalize effectively across diverse populations and environments, much like human intelligence.
A Condition Number for Joint Optimization of Cycle-Consistent Networks
Leonidas J. Guibas, Qixing Huang, Zhenxiao Liang
Neural Information Processing Systems http://nips.cc/
Entropy and mutual information in models of deep neural networks
Marylou Gabrié, Andre Manoel, Clément Luneau, jean barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová
Neural Information Processing Systems http://nips.cc/
Hunting for Discriminatory Proxies in Linear Regression Models
Samuel Yeom, Anupam Datta, Matt Fredrikson
Neural Information Processing Systems http://nips.cc/
OptimizingGeneralizedPageRankMethodsfor Seed-ExpansionCommunityDetection
PageRank (PR), an algorithm originally proposed by Page et al. for ranking web-pages [1] has found manysuccessful applications, including community detection [2,3],linkprediction [4]and recommendersystemdesign[5,6].
GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
Then we could generally binarize the reduced feature map before fed into the GUST.
Limits of Private Learning with Access to Public Data
Raef Bassily, Shay Moran, Noga Alon
Neural Information Processing Systems http://nips.cc/