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09/07/2023
Multi-Modality Guidance Network For Missing Modality Inference
Multimodal models have gained significant success in recent years. Stand...
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06/13/2023
Taxonomy-Structured Domain Adaptation
Domain adaptation aims to mitigate distribution shifts among different d...
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01/18/2023
Label Inference Attack against Split Learning under Regression Setting
As a crucial building block in vertical Federated Learning (vFL), Split ...
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10/11/2022
UGformer for Robust Left Atrium and Scar Segmentation Across Scanners
Thanks to the capacity for long-range dependencies and robustness to irr...
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09/15/2022
Differentially Private Estimation of Hawkes Process
Point process models are of great importance in real world applications....
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06/16/2022
Differentially Private Multi-Party Data Release for Linear Regression
Differentially Private (DP) data release is a promising technique to dis...
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04/28/2022
Tag-assisted Multimodal Sentiment Analysis under Uncertain Missing Modalities
Multimodal sentiment analysis has been studied under the assumption that...
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02/07/2022
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
We investigate the role of noise in optimization algorithms for learning...
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12/10/2021
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation
Most existing vision-language pre-training methods focus on understandin...
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10/01/2021
Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum
Momentum method has been used extensively in optimizers for deep learnin...
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06/17/2021
Recovery under Side Constraints
This paper addresses sparse signal reconstruction under various types of...
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05/02/2021
GODSAC*: Graph Optimized DSAC* for Robot Relocalization
Deep learning based camera pose estimation from monocular camera images ...
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02/24/2021
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization
Numerous empirical evidences have corroborated the importance of noise i...
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12/18/2020
Regularized Attentive Capsule Network for Overlapped Relation Extraction
Distantly supervised relation extraction has been widely applied in know...
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06/23/2020
A Benchmarking Framework for Interactive 3D Applications in the Cloud
With the growing popularity of cloud gaming and cloud virtual reality (V...
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01/09/2020
On Computation and Generalization of Generative Adversarial Imitation Learning
Generative Adversarial Imitation Learning (GAIL) is a powerful and pract...
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12/24/2019
Online Quantification of Input Model Uncertainty by Two-Layer Importance Sampling
Stochastic simulation has been widely used to analyze the performance of...
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09/10/2019
Towards Understanding the Importance of Shortcut Connections in Residual Networks
Residual Network (ResNet) is undoubtedly a milestone in deep learning. R...
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09/07/2019
Towards Understanding the Importance of Noise in Training Neural Networks
Numerous empirical evidence has corroborated that the noise plays a cruc...
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08/21/2018
Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning
Extracting relations is critical for knowledge base completion and const...
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06/04/2018
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization
Asynchronous momentum stochastic gradient descent algorithms (Async-MSGD...
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02/14/2018
Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations
Momentum Stochastic Gradient Descent (MSGD) algorithm has been widely ap...
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06/03/2015