research
∙
08/15/2023
Teach LLMs to Personalize – An Approach inspired by Writing Education
Personalized text generation is an emerging research area that has attra...
share
research
∙
07/12/2023
Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering
Automated Machine Learning (AutoML) techniques have recently been introd...
research
∙
06/06/2023
ColdNAS: Search to Modulate for User Cold-Start Recommendation
Making personalized recommendation for cold-start users, who only have a...
research
∙
03/05/2023
Knowledge-Enhanced Semi-Supervised Federated Learning for Aggregating Heterogeneous Lightweight Clients in IoT
Federated learning (FL) enables multiple clients to train models collabo...
research
∙
01/08/2023
Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement
Time series forecasting has been a widely explored task of great importa...
research
∙
11/21/2022
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model
Large-scale Transformer models bring significant improvements for variou...
research
∙
10/31/2022
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning
Standard fine-tuning of large pre-trained language models (PLMs) for dow...
research
∙
07/04/2022
Distilling Ensemble of Explanations for Weakly-Supervised Pre-Training of Image Segmentation Models
While fine-tuning pre-trained networks has become a popular way to train...
research
∙
05/24/2022
AdaMix: Mixture-of-Adapter for Parameter-efficient Tuning of Large Language Models
Fine-tuning large-scale pre-trained language models to downstream tasks ...
research
∙
05/06/2022
Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization
Nonconvex regularization has been popularly used in low-rank matrix lear...
research
∙
12/15/2021
Omni-Roach: A legged robot capable of traversing multiple types of large obstacles and self-righting
Robots excel at avoiding obstacles but still struggle to traverse comple...
research
∙
12/15/2021
Environmental force sensing enables robots to traverse cluttered obstacles with interaction
Many applications require robots to move through terrain with large obst...
research
∙
10/30/2021
Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification
Short text classification is a fundamental task in natural language proc...
research
∙
10/12/2021
LiST: Lite Self-training Makes Efficient Few-shot Learners
We present a new method LiST for efficient fine-tuning of large pre-trai...
research
∙
10/06/2021
Exploring the Common Principal Subspace of Deep Features in Neural Networks
We find that different Deep Neural Networks (DNNs) trained with the same...
research
∙
09/20/2021
Tele-Operated Oropharyngeal Swab (TOOS) RobotEnabled by TSS Soft Hand for Safe and EffectiveCOVID-19 OP Sampling
The COVID-19 pandemic has imposed serious challenges in multiple perspec...
research
∙
09/12/2021
FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning
Federated Learning has shown great potentials for the distributed data u...
research
∙
09/11/2021
Learning from Language Description: Low-shot Named Entity Recognition via Decomposed Framework
In this work, we study the problem of named entity recognition (NER) in ...
research
∙
09/09/2021
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning
Federated Semi-Supervised Learning (FedSSL) has gained rising attention ...
research
∙
07/16/2021
Property-aware Adaptive Relation Networks for Molecular Property Prediction
Molecular property prediction plays a fundamental role in drug discovery...
research
∙
06/22/2021
Multimodal Emergent Fake News Detection via Meta Neural Process Networks
Fake news travels at unprecedented speeds, reaches global audiences and ...
research
∙
12/06/2020
FedSemi: An Adaptive Federated Semi-Supervised Learning Framework
Federated learning (FL) has emerged as an effective technique to co-trai...
research
∙
12/04/2020
A Benchmark Dataset for Understandable Medical Language Translation
In this paper, we introduce MedLane – a new human-annotated Medical Lang...
research
∙
10/07/2020
Adaptive Self-training for Few-shot Neural Sequence Labeling
Neural sequence labeling is an important technique employed for many Nat...
research
∙
08/16/2020
Efficient Knowledge Graph Validation via Cross-Graph Representation Learning
Recent advances in information extraction have motivated the automatic c...
research
∙
08/14/2020
Efficient Low-Rank Matrix Learning by Factorizable Nonconvex Regularization
Matrix learning is at the core of many machine learning problems. To enc...
research
∙
06/24/2020
AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
Can one build a knowledge graph (KG) for all products in the world? Know...
research
∙
06/15/2020
Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data
Product catalogs are valuable resources for eCommerce website. In the ca...
research
∙
04/21/2020
Decomposed Adversarial Learned Inference
Effective inference for a generative adversarial model remains an import...
research
∙
12/28/2019
Weak Supervision for Fake News Detection via Reinforcement Learning
Today social media has become the primary source for news. Via social me...
research
∙
04/10/2019
Few-shot Learning: A Survey
The quest of `can machines think' and `can machines do what human do' ar...
research
∙
03/08/2019
General Convolutional Sparse Coding with Unknown Noise
Convolutional sparse coding (CSC) can learn representative shift-invaria...
research
∙
04/27/2018
Online Convolutional Sparse Coding with Sample-Dependent Dictionary
Convolutional sparse coding (CSC) has been popularly used for the learni...
research
∙
06/21/2017
