15 citations · 40 across the 11 of their papers we have counts for
11 papers
ScienceFlow: A long-horizon agent for ML research, scientific discovery and beyond
Mingming Zhao, Jiqian Dong, Kangping Xu +16
Enabling LLM agents to sustain productive, stable, and goal-aligned research over extended horizons is a central challenge for autonomous machine learning and scientific discovery,…
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network
Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang +5
The mobile communication enabled by cellular networks is the one of the main foundations of our modern society. Optimizing the performance of cellular networks and providing massiv…
Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief
Kaiyang Guo, Yunfeng Shao, Yanhui Geng
Model-based offline reinforcement learning (RL) aims to find highly rewarding policy, by leveraging a previously collected static dataset and a dynamics model. While the dynamics m…
Node Copying: A Random Graph Model for Effective Graph Sampling
Florence Regol, Soumyasundar Pal, Jianing Sun +3
There has been an increased interest in applying machine learning techniques on relational structured-data based on an observed graph. Often, this graph is not fully representative…
Universality of parametric Coupling Flows over parametric diffeomorphisms
Junlong Lyu, Zhitang Chen, Chang Feng +5
Invertible neural networks based on Coupling Flows CFlows) have various applications such as image synthesis and data compression. The approximation universality for CFlows is of p…
Sparse Personalized Federated Learning
Xiaofeng Liu, Yinchuan Li, Qing Wang +3
Federated Learning (FL) is a collaborative machine learning technique to train a global model without obtaining clients' private data. The main challenges in FL are statistical div…
A Causal Direction Test for Heterogeneous Populations
Vahid Partovi Nia, Xinlin Li, Masoud Asgharian +3
A probabilistic expert system emulates the decision-making ability of a human expert through a directional graphical model. The first step in building such systems is to understand…
Node-Constrained Traffic Engineering: Theory and Applications
George Trimponias, Yan Xiao, Xiaorui Wu +2
Traffic engineering (TE) is a fundamental task in networking. Conventionally, traffic can take any path connecting the source and destination. Emerging technologies such as segment…
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models
Shoubo Hu, Zhitang Chen, Vahid Partovi Nia +2
The inference of the causal relationship between a pair of observed variables is a fundamental problem in science, and most existing approaches are based on one single causal model…
Centrality-based Middlepoint Selection for Traffic Engineering with Segment Routing
George Trimponias, Yan Xiao, Hong Xu +2
Segment routing is an emerging technology to simplify traffic engineering implementation in WANs. It expresses an end-to-end logical path as a sequence of segments through a set of…
Information-Theoretic Bounds for Performance of Resource-Constrained Communication Systems
Albert Y. S. Lam, Yanhui Geng, Victor O. K. Li
Resource-constrained systems are prevalent in communications. Such a system is composed of many components but only some of them can be allocated with resources such as time slots.…