Search Results for author:
Found 15 papers, 5 papers with code
A Long-Short Demands-Aware Model for Next-Item Recommendation
Recommending the right products is the central problem in recommender systems, but the right products should also be recommended at the right time to meet the demands of users, so as to maximize their values.
SC-LSTM: Learning Task-Specific Representations in Multi-Task Learning for Sequence Labeling
Multi-task learning (MTL) has been studied recently for sequence labeling.
An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation
This paper studies graph-based recommendation, where an interaction graph is constructed from historical records and is lever-aged to alleviate data sparsity and cold start problems.
Ranked #2 on
Click-Through Rate Prediction
on MovieLens 1M
Relation-aware Hierarchical Attention Framework for Video Question Answering
Video Question Answering (VideoQA) is a challenging video understanding task since it requires a deep understanding of both question and video.
Event-Triggered Distributed Model Predictive Control for Platoon Coordination at Hubs in a Transport System
This paper considers the problem of hub-based platoon coordination for a large-scale transport system, where trucks have individual utility functions to optimize.
A Pricing Rule for Third-Party Platoon Coordination Service Provider
To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network.
Approximate Dynamic Programming for Platoon Coordination under Hours-of-Service Regulations
In our problem, trucks have fixed routes in a transportation network and can wait at hubs along their routes to form platoons with others while fulfilling the driving and rest time constraints.
Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation
Some recent knowledge distillation based methods transfer knowledge from complex teacher models to shallow student models for accelerating the online model inference.
Rollout-Based Charging Strategy for Electric Trucks with Hours-of-Service Regulations (Extended Version)
We assume that a collection of charging and rest stations is given along a pre-planned route with known detours and that the problem data are deterministic.
EulerNet: Adaptive Feature Interaction Learning via Euler's Formula for CTR Prediction
EulerNet converts the exponential powers of feature interactions into simple linear combinations of the modulus and phase of the complex features, making it possible to adaptively learn the high-order feature interactions in an efficient way.
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs.
Large-Scale Multi-Fleet Platoon Coordination: A Dynamic Programming Approach
This paper presents a distributed framework for addressing multi-fleet platoon coordination in large transportation networks, where each truck has a fixed route and aims to maximize its own fleet's platooning profit by scheduling its waiting times at hubs.
Towards Graph Foundation Models: A Survey and Beyond
Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and several other domains.
Distributed Charging Coordination of Electric Trucks with Limited Charging Resources
Electric trucks usually need to charge their batteries during long-range delivery missions, and the charging times are often nontrivial.
Distributed Traffic Signal Control of Interconnected Intersections: A Two-Lane Traffic Network Model
A distributed model predictive control (MPC) method is then presented to assign the green times.
