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Not Too Close and Not Too Far Enforcing Monotonicity Requires Penalizing The Right Points
Not Too Close and Not Too Far Enforcing Monotonicity Requires Penalizing The Right Points
J. Monteiro, M. O. Ahmed, H. Hajimirsadeghi, and G. Mori. NeurIPS Workshop on eXplainable AI Approaches for Debugging and Diagnosis, 2021
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Max-Margin Adversarial Training: Direct Input Space Margin Maximization through Adversarial Training
Max-Margin Adversarial Training: Direct Input Space Margin Maximization through Adversarial Training
G. W. Ding, Y. Sharma, K. Lui, and R. Huang. International Conference on Learning Representations (ICLR), 2020
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Adapting Grad-CAM for Embedding Networks
Adapting Grad-CAM for Embedding Networks
L. Chen, J. Chen, H. Hajimirsadeghi, and G. Mori. Winter Conference on Applications of Computer Vision (WACV), 2020
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On the Effectiveness of Low Frequency Perturbations
On the Effectiveness of Low Frequency Perturbations
Y. Sharma, G. W. Ding, and M. Brubaker. International Joint Conference on Artificial Intelligence (IJCAI), 2019
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On the Sensitivity of Adversarial Robustness to Input Data Distributions
On the Sensitivity of Adversarial Robustness to Input Data Distributions
G. W. Ding, K. Y. C. Lui, T. Jin, L. Wang, and R. Huang. International Conference on Learning Representations (ICLR), 2019
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Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces
B. Wang, and N. Hegde. The Conference and Workshop on Neural Information Processing Systems (NeurIPS), 2019
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Private Q-Learning with Functional Noise in Continuous Spaces
Private Q-Learning with Functional Noise in Continuous Spaces
B. Wang, and N. Hegde. The Conference and Workshop on Neural Information Processing Systems (NeurIPS), 2019
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Compositional Hard Negatives for Visual Semantic Embeddings via an Adversary
Compositional Hard Negatives for Visual Semantic Embeddings via an Adversary
*A. J. Bose, *H. Ling, and Y. Cao. The Conference and Workshop on Neural Information Processing Systems (NeurIPS), 2018
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Adversarial Contrastive Estimation
Adversarial Contrastive Estimation
*A. J. Bose, *H. Ling, and *Y. Cao. Association for Computational Linguistics (ACL), 2018
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Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
Y. Cao, G. W. Ding, K. Lui, and R. Huang. International Conference on Learning Representations (ICLR), 2018
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