Publications (24)
Stability of Charge Collection Efficiency and Time Resolution in 4H-SiC PIN Diodes Under X-ray Irradiation
Jiaqi Zhou, Sen Zhao, Xiyuan Zhang +6
This study evaluates the radiation tolerance of a 4H-SiC PIN detector under X-ray irradiation up to \SI{2}{MGy} (Si) at \SI{160}{keV}. The detector features a fully epitaxial verti…
Multi-Granularity Position Embedding of Graphs via Granular-Ball for Link Prediction
Sen Zhao, Cheng Liu, Shuyin Xia +4
Link prediction aims to identify potential or future connections within a given graph structure. Position information is essential for link prediction, as it distinguishes homogene…
Charge Collection Performance of 4H-SiC LGAD
Sen Zhao, Keqi Wang, Kaibo Xie +4
The 4H-SiC material exhibits good detection performance, but there are still many problems like signal distortion and poor signal quality. The 4H-SiC low gain avalanche detector (L…
Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation
Sen Zhao, Wei Wei, Xian-Ling Mao +5
Conversational recommendation systems (CRS) aim to interactively acquire user preferences and accordingly recommend items to users. Accurately learning the dynamic user preferences…
A Significance Test for Graph-Constrained Estimation
Sen Zhao, Ali Shojaie
Graph-constrained estimation methods encourage similarities among neighboring covariates presented as nodes on a graph, which can result in more accurate estimations, especially in…
Topology of Reasoning: Retrieved Cell Complex-Augmented Generation for Textual Graph Question Answering
Sen Zhao, Lincheng Zhou, Yue Chen +1
Retrieval-Augmented Generation (RAG) enhances the reasoning ability of Large Language Models (LLMs) by dynamically integrating external knowledge, thereby mitigating hallucinations…
4H-SiC PIN detector for alpha particles from room temperature to 90 °C
Xingchen Li, Sen Zhao, Mengke Cai +5
In the field of high-energy particle detection, detectors operating in high-radiation environments primarily face high costs associated with power consumption and cooling systems.…
A recurrent neural network approach for remaining useful life prediction utilizing a novel trend features construction method
Sen Zhao, Yong Zhang, Shang Wang +2
Data-driven methods for remaining useful life (RUL) prediction normally learn features from a fixed window size of a priori of degradation, which may lead to less accurate predicti…
In Defense of the Indefensible: A Very Naive Approach to High-Dimensional Inference
Sen Zhao, Daniela Witten, Ali Shojaie
A great deal of interest has recently focused on conducting inference on the parameters in a high-dimensional linear model. In this paper, we consider a simple and very naïve two-…
Kernel-Penalized Regression for Analysis of Microbiome Data
Timothy W. Randolph, Sen Zhao, Wade Copeland +2
The analysis of human microbiome data is often based on dimension-reduced graphical displays and clustering derived from vectors of microbial abundances in each sample. Common to t…
Network Differential Connectivity Analysis
Sen Zhao, Stephen Ottinger, Suzanne Peck +2
Identifying differences in networks has become a canonical problem in many biological applications. Here, we focus on testing whether two Gaussian graphical models are the same. Ex…
Metric-Optimized Example Weights
Sen Zhao, Mahdi Milani Fard, Harikrishna Narasimhan +1
Real-world machine learning applications often have complex test metrics, and may have training and test data that are not identically distributed. Motivated by known connections b…
GBGC: Efficient and Adaptive Graph Coarsening via Granular-ball Computing
Shuyin Xia, Guan Wang, Gaojie Xu +2
The objective of graph coarsening is to generate smaller, more manageable graphs while preserving key information of the original graph. Previous work were mainly based on the pers…
Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning
Sen Zhao, Wei Wei, Yifan Liu +6
Conversational recommendation systems (CRS) aim to timely and proactively acquire user dynamic preferred attributes through conversations for item recommendation. In each turn of C…
The study of 4H-SiC LGAD after proton radiation
Sen Zhao, Jiaqi Zhou, Chenxi Fu +7
Silicon carbide (SiC) is a promising material for radiation monitoring in harsh environments, due to its low dark current, high breakdown voltage, high thermal conductivity, and ra…
Global Optimization Networks
Sen Zhao, Erez Louidor, Olexander Mangylov +1
We consider the problem of estimating a good maximizer of a black-box function given noisy examples. To solve such problems, we propose to fit a new type of function which we call…
Bridging SFT and RL: Dynamic Policy Optimization for Robust Reasoning
Taojie Zhu, Dongyang Xu, Ding Zou +4
Post-training paradigms for Large Language Models (LLMs), primarily Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), face a fundamental dilemma: SFT provides stability…
GBO:AMulti-Granularity Optimization Algorithm via Granular-ball for Continuous Problems
Shuyin Xia, Xinyu Lin, Guan Wang +4
Optimization problems aim to find the optimal solution, which is becoming increasingly complex and difficult to solve. Traditional evolutionary optimization methods always overlook…
Multi-Granularity Open Intent Classification via Adaptive Granular-Ball Decision Boundary
Yanhua Li, Xiaocao Ouyang, Chaofan Pan +6
Open intent classification is critical for the development of dialogue systems, aiming to accurately classify known intents into their corresponding classes while identifying unkno…
Multi-view Intent Disentangle Graph Networks for Bundle Recommendation
Sen Zhao, Wei Wei, Ding Zou +1
Bundle recommendation aims to recommend the user a bundle of items as a whole. Nevertheless, they usually neglect the diversity of the user's intents on adopting items and fail to…
Predicting on the Edge: Identifying Where a Larger Model Does Better
Taman Narayan, Heinrich Jiang, Sen Zhao +1
Much effort has been devoted to making large and more accurate models, but relatively little has been put into understanding which examples are benefiting from the added complexity…
Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training
Shuyin Xia, Xinjun Ma, Zhiyuan Liu +3
Graph Neural Networks (GNNs) have demonstrated significant achievements in processing graph data, yet scalability remains a substantial challenge. To address this, numerous graph c…
Distribution Embedding Networks for Generalization from a Diverse Set of Classification Tasks
Lang Liu, Mahdi Milani Fard, Sen Zhao
We propose Distribution Embedding Networks (DEN) for classification with small data. In the same spirit of meta-learning, DEN learns from a diverse set of training tasks with the g…
Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent +56
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a cen…