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08/20/2023
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning
Federated Learning (FL) is popular for its privacy-preserving and collab...
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04/14/2023
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding
Soft-thresholding has been widely used in neural networks. Its basic net...
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01/31/2023
GDOD: Effective Gradient Descent using Orthogonal Decomposition for Multi-Task Learning
Multi-task learning (MTL) aims at solving multiple related tasks simulta...
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01/30/2023
Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization
To achieve scalable and accurate inference for latent Gaussian processes...
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12/29/2022
A Dynamics Theory of Implicit Regularization in Deep Low-Rank Matrix Factorization
Implicit regularization is an important way to interpret neural networks...
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12/04/2022
RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement Learning
Whole-slide images (WSI) in computational pathology have high resolution...
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12/02/2022
JAX-FEM: A differentiable GPU-accelerated 3D finite element solver for automatic inverse design and mechanistic data science
This paper introduces JAX-FEM, an open-source differentiable finite elem...
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08/15/2022
Locally anisotropic covariance functions on the sphere
Rapid developments in satellite remote-sensing technology have enabled t...
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06/15/2022
Hybrid full-field thermal characterization of additive manufacturing processes using physics-informed neural networks with data
Understanding the thermal behavior of additive manufacturing (AM) proces...
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04/26/2022
RAPQ: Rescuing Accuracy for Power-of-Two Low-bit Post-training Quantization
We introduce a Power-of-Two post-training quantization( PTQ) method for ...
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02/25/2022
Scalable Gaussian-process regression and variable selection using Vecchia approximations
Gaussian process (GP) regression is a flexible, nonparametric approach t...
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11/05/2021
MetaFEM: A Generic FEM Solver By Meta-expressions
Current multi-physics Finite Element Method (FEM) solvers are complex sy...
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07/22/2021
Additive manufacturing process design with differentiable simulations
We present a novel computational paradigm for process design in manufact...
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04/19/2021
TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers
At present, most research on the fairness of recommender systems is cond...
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02/24/2021
Dynamic Social Media Monitoring for Fast-Evolving Online Discussions
Tracking and collecting fast-evolving online discussions provides vast d...
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12/02/2020
FAST: A Fairness Assured Service Recommendation Strategy Considering Service Capacity Constraint
An excessive number of customers often leads to a degradation in service...
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12/02/2020
An Once-for-All Budgeted Pruning Framework for ConvNets Considering Input Resolution
We propose an efficient once-for-all budgeted pruning framework (OFARPru...
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11/29/2020
Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks
In order to deploy deep convolutional neural networks (CNNs) on resource...
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09/30/2020
Toolpath design for additive manufacturing using deep reinforcement learning
Toolpath optimization of metal-based additive manufacturing processes is...
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09/03/2020
Scalable computation of predictive probabilities in probit models with Gaussian process priors
Predictive models for binary data are fundamental in various fields, and...
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05/05/2020
Reliable and Efficient Long-Term Twitter Monitoring
Social media data is now widely used by many academic researchers. Howev...
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03/25/2020
Exploiting Low Rank Covariance Structures for Computing High-Dimensional Normal and Student-t Probabilities
We present a preconditioned Monte Carlo method for computing high-dimens...
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07/28/2019
A real-time iterative machine learning approach for temperature profile prediction in additive manufacturing processes
Additive Manufacturing (AM) is a manufacturing paradigm that builds thre...
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07/23/2019
