research
∙
09/06/2023
Epi-Curriculum: Episodic Curriculum Learning for Low-Resource Domain Adaptation in Neural Machine Translation
Neural Machine Translation (NMT) models have become successful, but thei...
share
research
∙
09/03/2023
MedChatZH: a Better Medical Adviser Learns from Better Instructions
Generative large language models (LLMs) have shown great success in vari...
research
∙
07/10/2023
FedYolo: Augmenting Federated Learning with Pretrained Transformers
The growth and diversity of machine learning applications motivate a ret...
research
∙
06/02/2023
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation
Stochastic approximation with multiple coupled sequences (MSA) has found...
research
∙
04/26/2023
Understand the Dynamic World: An End-to-End Knowledge Informed Framework for Open Domain Entity State Tracking
Open domain entity state tracking aims to predict reasonable state chang...
research
∙
12/29/2022
SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering
Deep learning has been widely used for protein engineering. However, it ...
research
∙
05/28/2022
MC-GEN:Multi-level Clustering for Private Synthetic Data Generation
Nowadays, machine learning is one of the most common technology to turn ...
research
∙
05/04/2022
FEDNEST: Federated Bilevel, Minimax, and Compositional Optimization
Standard federated optimization methods successfully apply to stochastic...
research
∙
04/16/2022
A Hierarchical N-Gram Framework for Zero-Shot Link Prediction
Due to the incompleteness of knowledge graphs (KGs), zero-shot link pred...
research
∙
04/15/2022
Semantic Structure based Query Graph Prediction for Question Answering over Knowledge Graph
Building query graphs from natural language questions is an important st...
research
∙
03/03/2022
Provable and Efficient Continual Representation Learning
In continual learning (CL), the goal is to design models that can learn ...
research
∙
02/07/2022
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation
Deep learning often requires a large amount of data. In real-world appli...
research
∙
01/04/2022
AutoBalance: Optimized Loss Functions for Imbalanced Data
Imbalanced datasets are commonplace in modern machine learning problems....
research
∙
04/29/2021
Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Neural Architecture Search (NAS) is a popular method for automatically d...
research
∙
11/16/2020
On the Marginal Benefit of Active Learning: Does Self-Supervision Eat Its Cake?
Active learning is the set of techniques for intelligently labeling larg...
research
∙
06/19/2020
Exploring Weight Importance and Hessian Bias in Model Pruning
Model pruning is an essential procedure for building compact and computa...
research
∙
02/09/2020
Short Text Classification via Knowledge powered Attention with Similarity Matrix based CNN
Short text is becoming more and more popular on the web, such as Chat Me...
research
∙
02/05/2020
Multi-Fusion Chinese WordNet (MCW) : Compound of Machine Learning and Manual Correction
Princeton WordNet (PWN) is a lexicon-semantic network based on cognitive...
research
∙
06/12/2019
Generalization Guarantees for Neural Networks via Harnessing the Low-rank Structure of the Jacobian
Modern neural network architectures often generalize well despite contai...
research
∙
03/27/2019