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03/18/2023
DC-CCL: Device-Cloud Collaborative Controlled Learning for Large Vision Models
Many large vision models have been deployed on the cloud for real-time s...
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01/30/2023
Designing Ad Auctions with Private Constraints for Automated Bidding
In online advertising, automated bidding (auto-bidding) has become a wid...
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11/11/2022
One-Time Model Adaptation to Heterogeneous Clients: An Intra-Client and Inter-Image Attention Design
The mainstream workflow of image recognition applications is first train...
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10/27/2022
AutoAttention: Automatic Field Pair Selection for Attention in User Behavior Modeling
In Click-through rate (CTR) prediction models, a user's interest is usua...
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10/22/2022
ALT: Boosting Deep Learning Performance by Breaking the Wall between Graph and Operator Level Optimizations
Deep learning models rely on highly optimized tensor libraries for effic...
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10/21/2022
On-Device Model Fine-Tuning with Label Correction in Recommender Systems
To meet the practical requirements of low latency, low cost, and good pr...
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09/01/2022
Online Data Selection for Federated Learning with Limited Storage
Machine learning models have been deployed in mobile networks to deal wi...
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06/01/2022
HIEN: Hierarchical Intention Embedding Network for Click-Through Rate Prediction
Click-through rate (CTR) prediction plays an important role in online ad...
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05/30/2022
Walle: An End-to-End, General-Purpose, and Large-Scale Production System for Device-Cloud Collaborative Machine Learning
To break the bottlenecks of mainstream cloud-based machine learning (ML)...
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04/25/2022
Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach
Collaborative filtering (CF), as a standard method for recommendation wi...
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02/20/2022
Cross-Task Knowledge Distillation in Multi-Task Recommendation
Multi-task learning (MTL) has been widely used in recommender systems, w...
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02/09/2022
Vertical Federated Learning: Challenges, Methodologies and Experiments
Recently, federated learning (FL) has emerged as a promising distributed...
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01/24/2022
On-Device Learning with Cloud-Coordinated Data Augmentation for Extreme Model Personalization in Recommender Systems
Data heterogeneity is an intrinsic property of recommender systems, maki...
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10/31/2021
FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social Networks
Finding influential users in social networks is a fundamental problem wi...
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09/16/2021
Federated Submodel Averaging
We study practical data characteristics underlying federated learning, w...
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06/13/2021
Hash Adaptive Bloom Filter
Bloom filter is a compact memory-efficient probabilistic data structure ...
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06/11/2021
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising
In online advertising, auto-bidding has become an essential tool for adv...
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06/07/2021
Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising
In e-commerce advertising, it is crucial to jointly consider various per...
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12/20/2020
Toward Understanding the Influence of Individual Clients in Federated Learning
Federated learning allows mobile clients to jointly train a global model...
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10/03/2020
Neighborhood Matters: Influence Maximization in Social Networks with Limited Access
Influence maximization (IM) aims at maximizing the spread of influence b...
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03/24/2020
UAVs as a Service: Boosting Edge Intelligence for Air-Ground Integrated Networks
The air-ground integrated network is a key component of future sixth gen...
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02/18/2020
Distributed Optimization over Block-Cyclic Data
We consider practical data characteristics underlying federated learning...
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02/18/2020
MoTiAC: Multi-Objective Actor-Critics for Real-Time Bidding
Online real-time bidding (RTB) is known as a complex auction game where ...
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02/18/2020
Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability
Federated learning is a new distributed machine learning framework, wher...
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11/28/2019
Online Pricing with Reserve Price Constraint for Personal Data Markets
The society's insatiable appetites for personal data are driving the eme...
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11/18/2019
Mechanism Design with Predicted Task Revenue for Bike Sharing Systems
Bike sharing systems have been widely deployed around the world in recen...
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11/07/2019
A Hierarchical Optimizer for Recommendation System Based on Shortest Path Algorithm
Top-k Nearest Geosocial Keyword (T-kNGK) query on geosocial network is d...
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11/06/2019
Secure Federated Submodel Learning
Federated learning was proposed with an intriguing vision of achieving c...
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10/28/2019
Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling
We target modeling latent dynamics in high-dimension marked event sequen...
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08/26/2019
NETR-Tree: An Eifficient Framework for Social-Based Time-Aware Spatial Keyword Query
The prevalence of social media and the development of geo-positioning te...
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03/25/2019
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems
Social recommendation leverages social information to solve data sparsit...
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12/08/2018
Achieving Data Truthfulness and Privacy Preservation in Data Markets
As a significant business paradigm, many online information platforms ha...
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11/14/2018
Fine-Grained User Profiling for Personalized Task Matching in Mobile Crowdsensing
In mobile crowdsensing, finding the best match between tasks and users i...
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04/28/2018
QDR-Tree: An Efcient Index Scheme for Complex Spatial Keyword Query
With the popularity of mobile devices and the development of geo-positio...
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04/05/2018
ERA: Towards Privacy Preservation and Verifiability for Online Ad Exchanges
Ad exchanges are kind of the most popular online advertising marketplace...
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12/22/2017
DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity
Nowadays, events usually burst and are propagated online through multipl...
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10/16/2017