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09/14/2023
NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation
Learning a recommender system model from an item's raw modality features...
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09/13/2023
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
Recommender systems (RS) have achieved significant success by leveraging...
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08/04/2023
Model Provenance via Model DNA
Understanding the life cycle of the machine learning (ML) model is an in...
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07/12/2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
Causal disentanglement aims to uncover a representation of data using la...
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06/26/2023
Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing
Gaussian process regression (GPR) is a non-parametric model that has bee...
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05/24/2023
Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights
Adapters, a plug-in neural network module with some tunable parameters, ...
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05/19/2023
Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights
Text-based collaborative filtering (TCF) has become the mainstream appro...
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09/10/2022
Active Learning for Optimal Intervention Design in Causal Models
An important problem across disciplines is the discovery of intervention...
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06/29/2022
Decision Forest Based EMG Signal Classification with Low Volume Dataset Augmented with Random Variance Gaussian Noise
Electromyography signals can be used as training data by machine learnin...
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03/30/2022
Polarized deep diffractive neural network for classification, generation, multiplexing and de-multiplexing of orbital angular momentum modes
The multiplexing and de-multiplexing of orbital angular momentum (OAM) b...
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01/19/2022
RunnerDNA: Interpretable indicators and model to characterize human activity pattern and individual difference
Human activity analysis based on sensor data plays a significant role in...
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11/26/2021
Simple Contrastive Representation Adversarial Learning for NLP Tasks
Self-supervised learning approach like contrastive learning is attached ...
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11/09/2021
Machine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectives
Background: Electronic Health Records (EHRs) contain rich information of...
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07/28/2021
Subjective evaluation of traditional and learning-based image coding methods
We conduct a subjective experiment to compare the performance of traditi...
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07/05/2021
Matching a Desired Causal State via Shift Interventions
Transforming a causal system from a given initial state to a desired tar...
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05/14/2021
Innovation Compression for Communication-efficient Distributed Optimization with Linear Convergence
Information compression is essential to reduce communication cost in dis...
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04/12/2021
Optimizing the Whole-life Cost in End-to-end CNN Acceleration
The acceleration of CNNs has gained increasing atten-tion since their su...
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09/02/2020
DARWIN: A Highly Flexible Platform for Imaging Research in Radiology
To conduct a radiomics or deep learning research experiment, the radiolo...
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03/29/2020
Defect segmentation: Mapping tunnel lining internal defects with ground penetrating radar data using a convolutional neural network
This research proposes a Ground Penetrating Radar (GPR) data processing ...
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03/01/2020
Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks
This paper proposes a fully asynchronous scheme for policy evaluation of...
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02/18/2020
Distributed Adaptive Newton Methods with Globally Superlinear Convergence
This paper considers the distributed optimization problem over a network...
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11/29/2019
Fast and Scalable Estimator for Sparse and Unit-Rank Higher-Order Regression Models
Because tensor data appear more and more frequently in various scientifi...
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11/29/2019
Sparse and Low-Rank Tensor Regression via Parallel Proximal Method
Motivated by applications in various scientific fields having demand of ...
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09/22/2019
Distributed Conjugate Gradient Tracking for Resource Allocation in Unbalanced Networks
This paper proposes a distributed conjugate gradient tracking algorithm ...
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09/06/2019
Decentralized Stochastic Gradient Tracking for Non-convex Empirical Risk Minimization
This paper studies a decentralized stochastic gradient tracking (DSGT) a...
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09/06/2019
Decentralized Stochastic Gradient Tracking for Empirical Risk Minimization
Recent works have shown superiorities of decentralized SGD to centralize...
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02/12/2019
A system for generating complex physically accurate sensor images for automotive applications
We describe an open-source simulator that creates sensor irradiance and ...
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01/24/2019
Asynchronous Decentralized Optimization in Directed Networks
A popular asynchronous protocol for decentralized optimization is random...
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11/01/2018
Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks
Semantic segmentation is one of the basic topics in computer vision, it ...
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08/13/2018
AsySPA: An Exact Asynchronous Algorithm for Convex Optimization Over Digraphs
This paper proposes a novel exact asynchronous subgradient-push algorith...
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03/29/2017