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06/08/2023
Expanding Scope: Adapting English Adversarial Attacks to Chinese
Recent studies have revealed that NLP predictive models are vulnerable t...
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05/02/2023
PGrad: Learning Principal Gradients For Domain Generalization
Machine learning models fail to perform when facing out-of-distribution ...
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02/03/2023
Improving Interpretability via Explicit Word Interaction Graph Layer
Recent NLP literature has seen growing interest in improving model inter...
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12/01/2022
Launchpad: Learning to Schedule Using Offline and Online RL Methods
Deep reinforcement learning algorithms have succeeded in several challen...
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11/22/2022
On the Transferability of Visual Features in Generalized Zero-Shot Learning
Generalized Zero-Shot Learning (GZSL) aims to train a classifier that ca...
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11/10/2022
RARE: Renewable Energy Aware Resource Management in Datacenters
The exponential growth in demand for digital services drives massive dat...
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05/10/2022
White-box Testing of NLP models with Mask Neuron Coverage
Recent literature has seen growing interest in using black-box strategie...
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10/29/2021
Estimating and Maximizing Mutual Information for Knowledge Distillation
In this work, we propose Mutual Information Maximization Knowledge Disti...
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10/10/2021
A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise Datasets
Recent Offline Reinforcement Learning methods have succeeded in learning...
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09/27/2021
ST-MAML: A Stochastic-Task based Method for Task-Heterogeneous Meta-Learning
Optimization-based meta-learning typically assumes tasks are sampled fro...
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09/24/2021
Long-Range Transformers for Dynamic Spatiotemporal Forecasting
Multivariate Time Series Forecasting (TSF) focuses on the prediction of ...
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09/01/2021
Towards Improving Adversarial Training of NLP Models
Adversarial training, a method for learning robust deep neural networks,...
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08/11/2021
Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing
Interpretability methods like Integrated Gradient and LIME are popular c...
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06/16/2021
Evolving Image Compositions for Feature Representation Learning
Convolutional neural networks for visual recognition require large amoun...
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06/16/2021
Towards Automatic Actor-Critic Solutions to Continuous Control
Model-free off-policy actor-critic methods are an efficient solution to ...
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03/03/2021
Relate and Predict: Structure-Aware Prediction with Jointly Optimized Neural DAG
Understanding relationships between feature variables is one important w...
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11/27/2020
General Multi-label Image Classification with Transformers
Multi-label image classification is the task of predicting a set of labe...
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10/13/2020
Measuring Visual Generalization in Continuous Control from Pixels
Self-supervised learning and data augmentation have significantly reduce...
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10/05/2020
TextAttack: Lessons learned in designing Python frameworks for NLP
TextAttack is an open-source Python toolkit for adversarial attacks, adv...
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04/29/2020
TextAttack: A Framework for Adversarial Attacks in Natural Language Processing
TextAttack is a library for running adversarial attacks against natural ...
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04/25/2020
Reevaluating Adversarial Examples in Natural Language
State-of-the-art attacks on NLP models have different definitions of wha...
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04/24/2020
Differential Network Learning Beyond Data Samples
Learning the change of statistical dependencies between random variables...
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01/16/2020
Curriculum Labeling: Self-paced Pseudo-Labeling for Semi-Supervised Learning
Semi-supervised learning aims to take advantage of a large amount of unl...
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04/17/2019
Neural Message Passing for Multi-Label Classification
Multi-label classification (MLC) is the task of assigning a set of targe...
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07/10/2018
DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications
Computational methods that predict differential gene expression from his...
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06/01/2018
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
We consider the problem of including additional knowledge in estimating ...
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01/13/2018
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers
Although various techniques have been proposed to generate adversarial s...
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10/30/2017
Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification
One of the fundamental tasks in understanding genomics is the problem of...
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10/30/2017
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure
We focus on the problem of estimating the change in the dependency struc...
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08/01/2017
Adversarial-Playground: A Visualization Suite Showing How Adversarial Examples Fool Deep Learning
Recent studies have shown that attackers can force deep learning models ...
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08/01/2017
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
The past decade has seen a revolution in genomic technologies that enabl...
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06/06/2017
Adversarial-Playground: A Visualization Suite for Adversarial Sample Generation
With growing interest in adversarial machine learning, it is important f...
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04/24/2017
GaKCo: a Fast GApped k-mer string Kernel using COunting
String Kernel (SK) techniques, especially those using gapped k-mers as f...
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04/04/2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Although deep neural networks (DNNs) have achieved great success in many...
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02/22/2017
DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples
Recent studies have shown that deep neural networks (DNN) are vulnerable...
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02/22/2017
Memory Matching Networks for Genomic Sequence Classification
When analyzing the genome, researchers have discovered that proteins bin...
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02/09/2017
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models
Estimating multiple sparse Gaussian Graphical Models (sGGMs) jointly for...
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12/01/2016
A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Examples
Most machine learning classifiers, including deep neural networks, are v...
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08/12/2016
Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks
Deep neural network (DNN) models have recently obtained state-of-the-art...
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05/11/2016
A constrained L1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models
Identifying context-specific entity networks from aggregated data is an ...
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12/20/2013