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Found 4 papers, 0 papers with code
Algorithmic Decision-Making under Agents with Persistent Improvement
We also extend the model to settings where 1) agents may be dishonest and game the algorithm into making favorable but erroneous decisions; 2) honest efforts are forgettable and not sufficient to guarantee persistent improvements.
Convergence Analysis for Learning Orthonormal Deep Linear Neural Networks
Enforcing orthonormal or isometric property for the weight matrices has been shown to enhance the training of deep neural networks by mitigating gradient exploding/vanishing and increasing the robustness of the learned networks.
Prototype Fission: Closing Set for Robust Open-set Semi-supervised Learning
Instead of "opening set", i. e., modeling OOD distribution, Prototype Fission "closes set" and makes it hard for OOD samples to fit in sub-class latent space.
Learning to Detect Critical Nodes in Sparse Graphs via Feature Importance Awareness
The critical node problem (CNP) aims to find a set of critical nodes from a network whose deletion maximally degrades the pairwise connectivity of the residual network.
