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09/14/2023
SMARTFEAT: Efficient Feature Construction through Feature-Level Foundation Model Interactions
Before applying data analytics or machine learning to a data set, a vita...
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09/05/2023
Data-Juicer: A One-Stop Data Processing System for Large Language Models
The immense evolution in Large Language Models (LLMs) has underscored th...
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09/01/2023
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning
LLMs have demonstrated great capabilities in various NLP tasks. Differen...
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08/29/2023
Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation
Large language models (LLMs) have emerged as a new paradigm for Text-to-...
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07/16/2023
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study
Despite the superior performance, Large Language Models (LLMs) require s...
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07/05/2023
SoK: Privacy-Preserving Data Synthesis
As the prevalence of data analysis grows, safeguarding data privacy has ...
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05/04/2023
Efficient Personalized Federated Learning via Sparse Model-Adaptation
Federated Learning (FL) aims to train machine learning models for multip...
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03/23/2023
FS-Real: Towards Real-World Cross-Device Federated Learning
Federated Learning (FL) aims to train high-quality models in collaborati...
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02/03/2023
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks
In this work, besides improving prediction accuracy, we study whether pe...
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12/12/2022
Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning
The increasing privacy concerns on personal private text data promote th...
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06/13/2022
Towards Universal Sequence Representation Learning for Recommender Systems
In order to develop effective sequential recommenders, a series of seque...
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06/11/2022
Sampling-based Estimation of the Number of Distinct Values in Distributed Environment
In data mining, estimating the number of distinct values (NDV) is a fund...
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06/08/2022
FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization
Hyperparameter optimization (HPO) is crucial for machine learning algori...
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06/08/2022
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning
Personalized Federated Learning (pFL), which utilizes and deploys distin...
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06/07/2022
Federated Hetero-Task Learning
To investigate the heterogeneity of federated learning in real-world sce...
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06/06/2022
ID-Agnostic User Behavior Pre-training for Sequential Recommendation
Recently, sequential recommendation has emerged as a widely studied topi...
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05/27/2022
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks
Graph Neural Networks (GNNs) have received extensive research attention ...
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04/12/2022
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
The incredible development of federated learning (FL) has benefited vari...
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04/11/2022
FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing
Although remarkable progress has been made by the existing federated lea...
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04/01/2022
Proactively Control Privacy in Recommender Systems
Recently, privacy issues in web services that rely on users' personal da...
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02/06/2022
Learning to be a Statistician: Learned Estimator for Number of Distinct Values
Estimating the number of distinct values (NDV) in a column is useful for...
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01/18/2022
Recommendation Unlearning
Recommender systems provide essential web services by learning users' pe...
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12/27/2021
Towards Personalized Answer Generation in E-Commerce via Multi-Perspective Preference Modeling
Recently, Product Question Answering (PQA) on E-Commerce platforms has a...
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08/30/2021
Factual Consistency Evaluation for Text Summarization via Counterfactual Estimation
Despite significant progress has been achieved in text summarization, fa...
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05/28/2021
CausCF: Causal Collaborative Filtering for RecommendationEffect Estimation
To improve user experience and profits of corporations, modern industria...
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05/20/2021
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning
Conversational recommender systems (CRS) enable the traditional recommen...
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03/05/2021
Competitive Information Disclosure with Multiple Receivers
This paper analyzes a model of competition in Bayesian persuasion in whi...
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01/09/2021
FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data
Interactive response time is important in analytical pipelines for users...
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01/04/2021
A Pluggable Learned Index Method via Sampling and Gap Insertion
Database indexes facilitate data retrieval and benefit broad application...
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10/27/2020
Contrastive Pre-training for Sequential Recommendation
Sequential recommendation methods play a crucial role in modern recommen...
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09/11/2020
Intertwining Order Preserving Encryption and Differential Privacy
Ciphertexts of an order-preserving encryption (OPE) scheme preserve the ...
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07/29/2020
Interactive Feature Generation via Learning Adjacency Tensor of Feature Graph
To automate the generation of interactive features, recent methods are p...
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07/04/2020
Simple and Deep Graph Convolutional Networks
Graph convolutional networks (GCNs) are a powerful deep learning approac...
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05/21/2020
Sequential Recommendation with Self-Attentive Multi-Adversarial Network
Recently, deep learning has made significant progress in the task of seq...
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04/07/2020
Practical Data Poisoning Attack against Next-Item Recommendation
Online recommendation systems make use of a variety of information sourc...
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01/13/2020
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search
Large pre-trained language models such as BERT have shown their effectiv...
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01/03/2020
Automated Relational Meta-learning
In order to efficiently learn with small amount of data on new tasks, me...
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09/25/2019
Design of Algorithms under Policy-Aware Local Differential Privacy: Utility-Privacy Trade-offs
Local differential privacy (LDP) enables private data sharing and analyt...
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08/30/2019
MURS: Practical and Robust Privacy Amplification with Multi-Party Differential Privacy
When collecting information, local differential privacy (LDP) alleviates...
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08/30/2019
Practical and Robust Privacy Amplification with Multi-Party Differential Privacy
When collecting information, local differential privacy (LDP) alleviates...
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03/01/2019
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment
Continuous integration is an indispensable step of modern software engin...
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11/08/2018
Efficient Identification of Approximate Best Configuration of Training in Large Datasets
A configuration of training refers to the combinations of feature engine...
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10/10/2018
Towards Differentially Private Truth Discovery for Crowd Sensing Systems
Nowadays, crowd sensing becomes increasingly more popular due to the ubi...
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07/02/2018
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Differential privacy has emerged as the main definition for private data...
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03/24/2018
Comparing Population Means under Local Differential Privacy: with Significance and Power
A statistical hypothesis test determines whether a hypothesis should be ...
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12/05/2017
Collecting Telemetry Data Privately
The collection and analysis of telemetry data from users' devices is rou...
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04/16/2017