2021-07
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Information Obfuscation of Graph Neural Networks
2021-06
2021-05
Understanding and Mitigating Accuracy Disparity in Regression
Decomposing Mutual Information for Representation Learning
Fundamental Limits and Tradeoffs in Invariant Representation Learning
Graph Adversarial Networks: Protecting Information against Adversarial Attacks
2021-03
Successor Feature Sets: Generalizing Successor Representations Across Policies
2021-02
Understanding and Mitigating Accuracy Disparity in Regression
2020-12
Domain adaptation with conditional distribution matching and generalized label shift
2020-11
An Empirical Investigation of Beam-Aware Training in Supertagging.
2020-05
De-Aliasing States In Dialogue Modelling With Inverse Reinforcement Learning
2020-04
Conditional Learning of Fair Representations
Learning General Latent-Variable Graphical Models with Predictive Belief Propagation
2020-03
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift. (arXiv:2003.04475v1 [cs.LG])
arXiv Computer Science
(2020-03-11)
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
2020-01
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation
2019-12
Expressiveness and Learning of Hidden Quantum Markov Models
AISTATS 2019
(2019-12-01)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:1912.02098 (2019-12-02)]2019-11
A Reduction from Reinforcement Learning to No-Regret Online Learning
AISTATS 2019
(2019-11-01)
proceedings.mlr.pressPDF[LATEST on arXiv preprint arXiv:1911.05873 (2019-11-14)]2019-09
Towards modular and programmable architecture search
Adversarial Privacy Preservation under Attribute Inference Attack
2019-07
Learning Neural Networks with Adaptive Regularization
2019-06
Adversarial Task-Specific Privacy Preservation under Attribute Attack.
2019-05
On learning invariant representations for domain adaptation
Deep Generative and Discriminative Domain Adaptation
2019-01
On Learning Invariant Representation for Domain Adaptation
Towards modular and programmable architecture search
Inherent Tradeoffs in Learning Fair Representations
2018-12
Dual Policy Iteration
Learning Beam Search Policies via Imitation Learning
Adversarial Multiple Source Domain Adaptation
2018-09
An Empirical Study of Example Forgetting during Deep Neural Network Learning
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