Search Results for author: Deng Pan

Found 5 papers, 3 papers with code

Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints

1 code implementation14 Dec 2020 Xin Li, Xiangrui Li, Deng Pan, Dongxiao Zhu

This inspires us to propose a new Probabilistically Compact (PC) loss with logit constraints which can be used as a drop-in replacement for cross-entropy (CE) loss to improve CNN's adversarial robustness.

Adversarial Robustness

Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability

no code implementations12 Jul 2020 Deng Pan, Xiangrui Li, Xin Li, Dongxiao Zhu

Latent factor collaborative filtering (CF) has been a widely used technique for recommender system by learning the semantic representations of users and items.

Collaborative Filtering Explainable Recommendation +1

Defending against adversarial attacks on medical imaging AI system, classification or detection?

1 code implementation24 Jun 2020 Xin Li, Deng Pan, Dongxiao Zhu

Medical imaging AI systems such as disease classification and segmentation are increasingly inspired and transformed from computer vision based AI systems.

Adversarial Defense General Classification

On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks

1 code implementation4 Mar 2020 Xiangrui Li, Xin Li, Deng Pan, Dongxiao Zhu

Deep convolutional neural networks (CNNs) trained with logistic and softmax losses have made significant advancement in visual recognition tasks in computer vision.

Classification General Classification +1

Improve SGD Training via Aligning Mini-batches

no code implementations23 Feb 2020 Xiangrui Li, Deng Pan, Xin Li, Dongxiao Zhu

In each iteration of SGD, a mini-batch from the training data is sampled and the true gradient of the loss function is estimated as the noisy gradient calculated on this mini-batch.

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