research
∙
09/18/2023
Stabilizing RLHF through Advantage Model and Selective Rehearsal
Large Language Models (LLMs) have revolutionized natural language proces...
share
research
∙
08/15/2023
EQ-Net: Elastic Quantization Neural Networks
Current model quantization methods have shown their promising capability...
research
∙
08/04/2023
VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs
Graph Neural Networks (GNNs) conduct message passing which aggregates lo...
research
∙
07/28/2023
Improving Social Media Popularity Prediction with Multiple Post Dependencies
Social Media Popularity Prediction has drawn a lot of attention because ...
research
∙
07/21/2023
Robust Fully-Asynchronous Methods for Distributed Training over General Architecture
Perfect synchronization in distributed machine learning problems is inef...
research
∙
07/10/2023
Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture Search
Cognitive diagnosis plays a vital role in modern intelligent education p...
research
∙
06/11/2023
RestGPT: Connecting Large Language Models with Real-World Applications via RESTful APIs
Tool-augmented large language models (LLMs) have achieved remarkable pro...
research
∙
03/31/2023
Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
Representation multi-task learning (MTL) and transfer learning (TL) have...
research
∙
02/05/2023
ℓ_1-penalized Multinomial Regression: Estimation, inference, and prediction, with an application to risk factor identification for different dementia subtypes
High-dimensional multinomial regression models are very useful in practi...
research
∙
12/09/2022
DUNE: Improving Accuracy for Sketch-INT Network Measurement Systems
In-band Network Telemetry (INT) and sketching algorithms are two promisi...
research
∙
09/30/2022
Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
Unsupervised learning has been widely used in many real-world applicatio...
research
∙
08/08/2022
Deep Maxout Network Gaussian Process
Study of neural networks with infinite width is important for better und...
research
∙
07/13/2022
Semi-supervised Ranking for Object Image Blur Assessment
Assessing the blurriness of an object image is fundamentally important t...
research
∙
06/26/2022
Detecting Schizophrenia with 3D Structural Brain MRI Using Deep Learning
Schizophrenia is a chronic neuropsychiatric disorder that causes distinc...
research
∙
04/28/2022
How social influence affects the wisdom of crowds in influence networks
A long-standing debate is whether social influence improves the collecti...
research
∙
02/02/2022
GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs
Fueled by advances in distributed deep learning (DDL), recent years have...
research
∙
01/21/2022
Improving Across-Dataset Brain Tissue Segmentation Using Transformer
Brain tissue segmentation has demonstrated great utility in quantifying ...
research
∙
12/16/2021
APTSHIELD: A Stable, Efficient and Real-time APT Detection System for Linux Hosts
Advanced Persistent Threat (APT) attack usually refers to the form of lo...
research
∙
11/08/2021
Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
Most existing classification methods aim to minimize the overall misclas...
research
∙
09/29/2021
CCTrans: Simplifying and Improving Crowd Counting with Transformer
Most recent methods used for crowd counting are based on the convolution...
research
∙
08/10/2021
Accelerating Evolutionary Neural Architecture Search via Multi-Fidelity Evaluation
Evolutionary neural architecture search (ENAS) has recently received inc...
research
∙
07/19/2021
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Crowd counting on the drone platform is an interesting topic in computer...
research
∙
05/29/2021
Transfer Learning under High-dimensional Generalized Linear Models
In this work, we study the transfer learning problem under high-dimensio...
research
∙
05/22/2021
Principled Design of Translation, Scale, and Rotation Invariant Variation Operators for Metaheuristics
In the past three decades, a large number of metaheuristics have been pr...
research
∙
05/21/2021
Towards a Universal NLG for Dialogue Systems and Simulators with Future Bridging
In a dialogue system pipeline, a natural language generation (NLG) unit ...
research
∙
05/10/2021
AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference
This paper presents AppealNet, a novel edge/cloud collaborative architec...
research
∙
05/06/2021
Evaluating the Effect of Longitudinal Dose and INR Data on Maintenance Warfarin Dose Predictions
Warfarin, a commonly prescribed drug to prevent blood clots, has a highl...
research
∙
03/08/2021
Meta-Learning with MAML on Trees
In meta-learning, the knowledge learned from previous tasks is transferr...
research
∙
02/16/2021
A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images
Real-time magnetic resonance imaging (RT-MRI) of human speech production...
research
∙
02/07/2021
RaSE: A Variable Screening Framework via Random Subspace Ensembles
Variable screening methods have been shown to be effective in dimension ...
research
∙
01/02/2021
A Multilayer Correlated Topic Model
We proposed a novel multilayer correlated topic model (MCTM) to analyze ...
research
∙
09/21/2020
DeepDyve: Dynamic Verification for Deep Neural Networks
Deep neural networks (DNNs) have become one of the enabling technologies...
research
∙
08/10/2020
CG-SENSE revisited: Results from the first ISMRM reproducibility challenge
Purpose: The aim of this work is to shed light on the issue of reproduci...
research
∙
06/16/2020
RaSE: Random Subspace Ensemble Classification
We propose a new model-free ensemble classification framework, Random Su...
research
∙
04/08/2020
Downstream Model Design of Pre-trained Language Model for Relation Extraction Task
Supervised relation extraction methods based on deep neural network play...
research
∙
02/25/2020
Distributed Algorithms for Composite Optimization: Unified Framework and Convergence Analysis
We study distributed composite optimization over networks: agents minimi...
research
∙
02/25/2020
Distributed Algorithms for Composite Optimization: Unified and Tight Convergence Analysis
We study distributed composite optimization over networks: agents minimi...
research
∙
10/23/2019
Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
This paper proposes a novel family of primal-dual-based distributed algo...
research
∙
08/28/2019
Learning a Multitask Curriculum for Neural Machine Translation
Existing curriculum learning research in neural machine translation (NMT...
research
∙
05/30/2019
DeepShift: Towards Multiplication-Less Neural Networks
Deep learning models, especially DCNN have obtained high accuracies in s...
research
∙
05/27/2019
Computer-aided Detection of Squamous Carcinoma of the Cervix in Whole Slide Images
Goal: Squamous cell carcinoma of cervix is one of the most prevalent can...
research
∙
02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
research
∙
11/07/2018
THORS: An Efficient Approach for Making Classifiers Cost-sensitive
In this paper, we propose an effective THresholding method based on ORde...
research
∙
07/24/2018
ClusterNet: Instance Segmentation in RGB-D Images
We propose a method for instance-level segmentation that uses RGB-D data...
research
∙
05/16/2018
Spatial Transformer Introspective Neural Network
Natural images contain many variations such as illumination differences,...
research
∙
03/28/2018
ASY-SONATA: Achieving Geometric Convergence for Distributed Asynchronous Optimization
Can one obtain a geometrically convergent algorithm for distributed asyn...
research
∙
01/04/2017