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06/24/2021
Label Disentanglement in Partition-based Extreme Multilabel Classification
Partition-based methods are increasingly-used in extreme multi-label cla...
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10/19/2020
How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers
Many optimizers have been proposed for training deep neural networks, an...
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08/07/2020
Improving the Speed and Quality of GAN by Adversarial Training
Generative adversarial networks (GAN) have shown remarkable results in i...
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06/12/2020
Provably Robust Metric Learning
Metric learning is an important family of algorithms for classification ...
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05/31/2020
Evaluations and Methods for Explanation through Robustness Analysis
Among multiple ways of interpreting a machine learning model, measuring ...
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03/13/2020
Learning to Encode Position for Transformer with Continuous Dynamical Model
We introduce a new way of learning to encode position information for no...
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02/19/2020
Gradient Boosting Neural Networks: GrowNet
A novel gradient boosting framework is proposed where shallow neural net...
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11/11/2019
GraphDefense: Towards Robust Graph Convolutional Networks
In this paper, we study the robustness of graph convolutional networks (...
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10/30/2019
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
In this paper, we proposed a general framework for data poisoning attack...
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06/10/2019
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective
We study the problem of computing the minimum adversarial perturbation o...
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06/05/2019
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise
Neural Ordinary Differential Equation (Neural ODE) has been proposed as ...
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05/20/2019
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Graph convolutional network (GCN) has been successfully applied to many ...
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10/01/2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
We present a new algorithm to train a robust neural network against adve...
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09/26/2018
Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient
Trust region and cubic regularization methods have demonstrated good per...
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08/07/2018
Fast Variance Reduction Method with Stochastic Batch Size
In this paper we study a family of variance reduction methods with rando...
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07/27/2018
From Adversarial Training to Generative Adversarial Networks
In this paper, we are interested in two seemingly different concepts: ad...
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12/02/2017
Towards Robust Neural Networks via Random Self-ensemble
Recent studies have revealed the vulnerability of deep neural networks -...
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08/28/2017