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09/21/2023
Spatial-Temporal Transformer based Video Compression Framework
Learned video compression (LVC) has witnessed remarkable advancements in...
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05/31/2023
MSMix:An Interpolation-Based Text Data Augmentation Method Manifold Swap Mixup
To solve the problem of poor performance of deep neural network models d...
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03/09/2023
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting
Balancing efficiency and accuracy is a long-standing problem for deployi...
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09/19/2022
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach
Bilevel optimization (BO) is useful for solving a variety of important m...
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09/02/2022
First Hitting Diffusion Models
We propose a family of First Hitting Diffusion Models (FHDM), deep gener...
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09/02/2022
Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems
One of the key challenges of learning an online recommendation model is ...
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09/02/2022
Diffusion-based Molecule Generation with Informative Prior Bridges
AI-based molecule generation provides a promising approach to a large ar...
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08/31/2022
Let us Build Bridges: Understanding and Extending Diffusion Generative Models
Diffusion-based generative models have achieved promising results recent...
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08/30/2022
Developing a Vehicle Re-routing Algorithm using Connected Vehicle (CV) Technology
Vehicle Ad-hoc Networks (VANETs) act as the core of vehicular communicat...
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08/23/2022
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results
This paper reviews the Challenge on Super-Resolution of Compressed Image...
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05/11/2022
Multi-Class 3D Object Detection with Single-Class Supervision
While multi-class 3D detectors are needed in many robotics applications,...
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04/29/2022
The scope for AI-augmented interpretation of building blueprints in commercial and industrial property insurance
This report, commissioned by the WTW research network, investigates the ...
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10/17/2021
Centroid Approximation for Bootstrap
Bootstrap is a principled and powerful frequentist statistical tool for ...
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10/17/2021
Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto Set
Many modern machine learning applications, such as multi-task learning, ...
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04/18/2021
FOX: Hardware-Assisted File Auditing for Direct Access NVM-Hosted Filesystems
With emerging non-volatile memories entering the mainstream market, seve...
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03/14/2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments
Motivated by the rising abundance of observational data with continuous ...
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10/29/2020
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough
Despite the great success of deep learning, recent works show that large...
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10/16/2020
Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data
Large scale deep learning provides a tremendous opportunity to improve t...
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05/29/2020
SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions
State-of-the-art NLP models can often be fooled by human-unaware transfo...
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05/29/2020
Unsupervised Feature Selection via Multi-step Markov Transition Probability
Feature selection is a widely used dimension reduction technique to sele...
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05/28/2020
Improving Generalized Zero-Shot Learning by Semantic Discriminator
It is a recognized fact that the classification accuracy of unseen class...
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05/28/2020
Disentanglement Then Reconstruction: Learning Compact Features for Unsupervised Domain Adaptation
Recent works in domain adaptation always learn domain invariant features...
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05/28/2020
Learning Various Length Dependence by Dual Recurrent Neural Networks
Recurrent neural networks (RNNs) are widely used as a memory model for s...
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03/23/2020
Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting
We propose signed splitting steepest descent (S3D), which progressively ...
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03/13/2020
Joint COCO and Mapillary Workshop at ICCV 2019 Keypoint Detection Challenge Track Technical Report: Distribution-Aware Coordinate Representation for Human Pose Estimation
In this paper, we focus on the coordinate representation in human pose e...
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03/03/2020
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
Recent empirical works show that large deep neural networks are often hi...
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02/21/2020
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
Randomized classifiers have been shown to provide a promising approach f...
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02/21/2020
Stein Self-Repulsive Dynamics: Benefits From Past Samples
We propose a new Stein self-repulsive dynamics for obtaining diversified...
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02/20/2020
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision
We consider the post-training quantization problem, which discretizes th...
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02/20/2020
MaxUp: A Simple Way to Improve Generalization of Neural Network Training
We propose MaxUp, an embarrassingly simple, highly effective technique f...
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02/07/2020
Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection
Stochastic gradient Markov chain Monte Carlo (MCMC) algorithms have rece...
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10/14/2019
Distribution-Aware Coordinate Representation for Human Pose Estimation
While being the de facto standard coordinate representation in human pos...
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11/13/2018
Fast Human Pose Estimation
Existing human pose estimation approaches often only consider how to imp...
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10/20/2018
Triad-NVM: Persistent-Security for Integrity-Protected and Encrypted Non-Volatile Memories (NVMs)
Emerging Non-Volatile Memories (NVMs) are promising contenders for build...
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10/08/2018
Stein Neural Sampler
We propose two novel samplers to produce high-quality samples from a giv...
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10/17/2017
Do Convolutional Neural Networks Learn Class Hierarchy?
Convolutional Neural Networks (CNNs) currently achieve state-of-the-art ...
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07/19/2017