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09/04/2023
Zero-shot information extraction from radiological reports using ChatGPT
Electronic health records contain an enormous amount of valuable informa...
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07/21/2023
Sensing Aided Covert Communications: Turning Interference into Allies
In this paper, we investigate the realization of covert communication in...
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03/14/2023
Gamora: Graph Learning based Symbolic Reasoning for Large-Scale Boolean Networks
Reasoning high-level abstractions from bit-blasted Boolean networks (BNs...
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01/21/2023
Improving Accuracy of Zero-Shot Action Recognition with Handcrafted Features
With the development of machine learning, datasets for models are gettin...
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01/09/2023
Privacy-Preserving Record Linkage for Cardinality Counting
Several applications require counting the number of distinct items in th...
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12/02/2022
A Closed-Form EVSI Expression for a Multinomial Data-Generating Process
This paper derives analytic expressions for the expected value of sample...
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09/02/2022
GReS: Graphical Cross-domain Recommendation for Supply Chain Platform
Supply Chain Platforms (SCPs) provide downstream industries with numerou...
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09/01/2022
Heterogeneous Graph Tree Networks
Heterogeneous graph neural networks (HGNNs) have attracted increasing re...
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07/13/2022
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation
Using machine learning to solve combinatorial optimization (CO) problems...
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06/30/2022
Fairness and Cost Constrained Privacy-Aware Record Linkage
Record linkage algorithms match and link records from different database...
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06/01/2022
Dog nose print matching with dual global descriptor based on Contrastive Learning
Recent studies in biometric-based identification tasks have shown that d...
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05/19/2022
Neural network topological snake models for locating general phase diagrams
Machine learning for locating phase diagram has received intensive resea...
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04/27/2022
GTNet: A Tree-Based Deep Graph Learning Architecture
We propose Graph Tree Networks (GTNets), a deep graph learning architect...
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02/10/2022
Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks
We hypothesize that due to the greedy nature of learning in multi-modal ...
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01/30/2022
Will Metaverse be NextG Internet? Vision, Hype, and Reality
Metaverse, with the combination of the prefix "meta" (meaning transcendi...
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01/20/2022
Hybrid Graph Models for Logic Optimization via Spatio-Temporal Information
Despite the stride made by machine learning (ML) based performance model...
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01/18/2022
High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing
Agile hardware development requires fast and accurate circuit quality ev...
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01/15/2022
Realtime 3D Object Detection for Headsets
Mobile headsets should be capable of understanding 3D physical environme...
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10/20/2021
SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training
Unsupervised pre-training is now the predominant approach for both text ...
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10/15/2021
Cooperative Localization in Massive Networks
Network localization is capable of providing accurate and ubiquitous pos...
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10/14/2021
Inferring Manifolds From Noisy Data Using Gaussian Processes
In analyzing complex datasets, it is often of interest to infer lower di...
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09/13/2021
Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation
Circuit design is complicated and requires extensive domain-specific exp...
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06/13/2021
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis
In the last few years, deep learning classifiers have shown promising re...
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02/16/2021
IronMan: GNN-assisted Design Space Exploration in High-Level Synthesis via Reinforcement Learning
Despite the great success of High-Level Synthesis (HLS) tools, we observ...
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02/16/2021
A Survey of Machine Learning for Computer Architecture and Systems
It has been a long time that computer architecture and systems are optim...
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01/25/2021
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation
This work studies the spectral convergence of graph Laplacian to the Lap...
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11/13/2020
Phoebe: Reuse-Aware Online Caching with Reinforcement Learning for Emerging Storage Models
With data durability, high access speed, low power efficiency and byte a...
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10/14/2020
Diffusion Based Gaussian Processes on Restricted Domains
In nonparametric regression and spatial process modeling, it is common f...
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09/19/2020
Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms
Breast cancer is the most common cancer in women, and hundreds of thousa...
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08/04/2020
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department
During the COVID-19 pandemic, rapid and accurate triage of patients at t...
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07/13/2020
Strong Uniform Consistency with Rates for Kernel Density Estimators with General Kernels on Manifolds
We provide a strong uniform consistency result with the convergence rate...
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05/22/2020
Data-driven Efficient Solvers and Predictions of Conformational Transitions for Langevin Dynamics on Manifold in High Dimensions
We work on dynamic problems with collected data {x_i} that distributed o...
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02/13/2020
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
Medical images differ from natural images in significantly higher resolu...
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01/20/2020
Memristor Hardware-Friendly Reinforcement Learning
Recently, significant progress has been made in solving sophisticated pr...
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12/11/2019
Diffusion based Gaussian process regression via heat kernel reconstruction
We propose an algorithm for Gaussian Process regression on an unknown em...
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08/01/2019
Improving localization-based approaches for breast cancer screening exam classification
We trained and evaluated a localization-based deep CNN for breast cancer...
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07/30/2019
Screening Mammogram Classification with Prior Exams
Radiologists typically compare a patient's most recent breast cancer scr...
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06/24/2019
The Value of Collaboration in Convex Machine Learning with Differential Privacy
In this paper, we apply machine learning to distributed private data own...
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06/07/2019
Globally-Aware Multiple Instance Classifier for Breast Cancer Screening
Deep learning models designed for visual classification tasks on natural...
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03/20/2019
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
We present a deep convolutional neural network for breast cancer screeni...
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11/11/2018
When Locally Linear Embedding Hits Boundary
Based on the Riemannian manifold model, we study the asymptotical behavi...
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10/01/2018
Network Modeling and Pathway Inference from Incomplete Data ("PathInf")
In this work, we developed a network inference method from incomplete da...
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04/09/2018
Connecting Dots -- from Local Covariance to Empirical Intrinsic Geometry and Locally Linear Embedding
Local covariance structure under the manifold setup has been widely appl...
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11/10/2017
Breast density classification with deep convolutional neural networks
Breast density classification is an essential part of breast cancer scre...
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03/07/2016