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03/09/2023
Open World Classification with Adaptive Negative Samples
Open world classification is a task in natural language processing with ...
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10/23/2022
Pushing the Efficiency Limit Using Structured Sparse Convolutions
Weight pruning is among the most popular approaches for compressing deep...
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10/17/2022
Pseudo-OOD training for robust language models
While pre-trained large-scale deep models have garnered attention as an ...
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09/20/2022
Collaborative Anomaly Detection
In recommendation systems, items are likely to be exposed to various use...
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05/07/2022
Number Entity Recognition
Numbers are essential components of text, like any other word tokens, fr...
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02/25/2022
Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations
End-to-end learning of dynamical systems with black-box models, such as ...
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11/24/2021
Explainable multiple abnormality classification of chest CT volumes with AxialNet and HiResCAM
Understanding model predictions is critical in healthcare, to facilitate...
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11/04/2021
Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping
Distributed learning has become an integral tool for scaling up machine ...
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11/04/2021
Variational Inference with Holder Bounds
The recent introduction of thermodynamic integration techniques has prov...
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07/09/2021
Hölder Bounds for Sensitivity Analysis in Causal Reasoning
We examine interval estimation of the effect of a treatment T on an outc...
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07/05/2021
Imputation-Free Learning from Incomplete Observations
Although recent works have developed methods that can generate estimatio...
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04/27/2021
Towards Fair Federated Learning with Zero-Shot Data Augmentation
Federated learning has emerged as an important distributed learning para...
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04/02/2021
Malignancy Prediction and Lesion Identification from Clinical Dermatological Images
We consider machine-learning-based malignancy prediction and lesion iden...
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03/25/2021
Efficient Feature Transformations for Discriminative and Generative Continual Learning
As neural networks are increasingly being applied to real-world applicat...
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03/17/2021
Improving Zero-shot Voice Style Transfer via Disentangled Representation Learning
Voice style transfer, also called voice conversion, seeks to modify one ...
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03/11/2021
FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders
Pretrained text encoders, such as BERT, have been applied increasingly i...
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03/06/2021
Efficient Continual Adaptation for Generative Adversarial Networks
We present a continual learning approach for generative adversarial netw...
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02/23/2021
Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning
Zero-shot learning (ZSL) has been shown to be a promising approach to ge...
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02/10/2021
FLOP: Federated Learning on Medical Datasets using Partial Networks
The outbreak of COVID-19 Disease due to the novel coronavirus has caused...
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01/17/2021
What Makes Good In-Context Examples for GPT-3?
GPT-3 has attracted lots of attention due to its superior performance ac...
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12/15/2020
Wasserstein Contrastive Representation Distillation
The primary goal of knowledge distillation (KD) is to encapsulate the in...
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12/10/2020
Learning Graphons via Structured Gromov-Wasserstein Barycenters
We propose a novel and principled method to learn a nonparametric graph ...
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12/06/2020
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models
Deep neural networks have shown significant promise in comprehending com...
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11/25/2020
Supercharging Imbalanced Data Learning With Causal Representation Transfer
Dealing with severe class imbalance poses a major challenge for real-wor...
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11/17/2020
HiResCAM: Explainable Multi-Organ Multi-Abnormality Prediction in 3D Medical Images
Understanding model predictions is critical in healthcare, to facilitate...
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11/09/2020
Estimating Total Correlation with Mutual Information Bounds
Total correlation (TC) is a fundamental concept in information theory to...
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11/01/2020
MixKD: Towards Efficient Distillation of Large-scale Language Models
Large-scale language models have recently demonstrated impressive empiri...
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10/23/2020
Counterfactual Representation Learning with Balancing Weights
A key to causal inference with observational data is achieving balance i...
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10/15/2020
Double Robust Representation Learning for Counterfactual Prediction
Causal inference, or counterfactual prediction, is central to decision m...
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10/15/2020
RetiNerveNet: Using Recursive Deep Learning to Estimate Pointwise 24-2 Visual Field Data based on Retinal Structure
Glaucoma is the leading cause of irreversible blindness in the world, af...
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10/12/2020
Improving Text Generation with Student-Forcing Optimal Transport
Neural language models are often trained with maximum likelihood estimat...
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10/02/2020
Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images
Recently, progress has been made in the supervised training of Convoluti...
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08/14/2020
Weakly supervised cross-domain alignment with optimal transport
Cross-domain alignment between image objects and text sequences is key t...
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08/13/2020
WAFFLe: Weight Anonymized Factorization for Federated Learning
In domains where data are sensitive or private, there is great value in ...
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07/13/2020
Bridging Maximum Likelihood and Adversarial Learning via α-Divergence
Maximum likelihood (ML) and adversarial learning are two popular approac...
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06/26/2020
Graph Optimal Transport for Cross-Domain Alignment
Cross-domain alignment between two sets of entities (e.g., objects in an...
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06/22/2020
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Mutual information (MI) minimization has gained considerable interests i...
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06/16/2020
GO Hessian for Expectation-Based Objectives
An unbiased low-variance gradient estimator, termed GO gradient, was pro...
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06/14/2020
Survival Analysis meets Counterfactual Inference
There is growing interest in applying machine learning methods for count...
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06/13/2020
GAN Memory with No Forgetting
Seeking to address the fundamental issue of memory in lifelong learning,...
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06/12/2020
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization
Control variates are a well-established tool to reduce the variance of M...
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06/04/2020
Hierarchical Optimal Transport for Robust Multi-View Learning
Traditional multi-view learning methods often rely on two assumptions: (...
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06/04/2020
Towards Understanding Fast Adversarial Training
Current neural-network-based classifiers are susceptible to adversarial ...
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06/01/2020
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance
Learning disentangled representations of natural language is essential f...
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05/08/2020
Y-Net for Chest X-Ray Preprocessing: Simultaneous Classification of Geometry and Segmentation of Annotations
Over the last decade, convolutional neural networks (CNNs) have emerged ...
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05/04/2020
Reward Constrained Interactive Recommendation with Natural Language Feedback
Text-based interactive recommendation provides richer user feedback and ...
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05/04/2020
Improving Adversarial Text Generation by Modeling the Distant Future
Auto-regressive text generation models usually focus on local fluency, a...
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04/30/2020
APo-VAE: Text Generation in Hyperbolic Space
Natural language often exhibits inherent hierarchical structure ingraine...
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04/29/2020
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
We consider the blackbox transfer-based targeted adversarial attack thre...
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04/27/2020
