Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN2.9k papers
- Centre National de la Recherche ScientifiqueFR2.7k papers
- Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiIT2.6k papers
- Institute of High Energy PhysicsCN2.6k papers
- University of Science and Technology of ChinaCN2.5k papers
- Peking UniversityCN2.4k papers
- University of Chinese Academy of SciencesCN2.3k papers
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma IIT2.3k papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR2.3k papers
- Rutherford Appleton LaboratoryGB2.2k papers
- Istituto Nazionale di Fisica Nucleare, Sezione di GenovaIT2.2k papers
- European Organization for Nuclear ResearchCH2.2k papers
30 papers · 2 filters
Fairness without Demographics through Learning Graph of Gradients
Yingtao Luo, Zhixun Li, Qiang Liu +1
Machine learning systems are notoriously prone to biased predictions about certain demographic groups, leading to algorithmic fairness issues. Due to privacy concerns and data qual…
Federated Split Learning with Model Pruning and Gradient Quantization in Wireless Networks
Junhe Zhang, Wanli Ni, Dongyu Wang
As a paradigm of distributed machine learning, federated learning typically requires all edge devices to train a complete model locally. However, with the increasing scale of artif…
Conformal Symplectic Optimization for Stable Reinforcement Learning
Yao Lyu, Xiangteng Zhang, Shengbo Eben Li +5
Training deep reinforcement learning (RL) agents necessitates overcoming the highly unstable nonconvex stochastic optimization inherent in the trial-and-error mechanism. To tackle…
Multimodal Information Bottleneck for Deep Reinforcement Learning with Multiple Sensors
Bang You, Huaping Liu
Reinforcement learning has achieved promising results on robotic control tasks but struggles to leverage information effectively from multiple sensory modalities that differ in man…
Syno: Structured Synthesis for Neural Operators
Yongqi Zhuo, Zhengyuan Su, Chenggang Zhao +1
The desires for better prediction accuracy and higher execution performance in neural networks never end. Neural architecture search (NAS) and tensor compilers are two popular tech…
Neuralink: Fast LLM Inference on Smartphones with Neuron Co-Activation Linking
Tuowei Wang, Ruwen Fan, Minxing Huang +6
Large Language Models (LLMs) have achieved remarkable success across various domains, yet deploying them on mobile devices remains an arduous challenge due to their extensive compu…
UoMo: A Universal Model of Mobile Traffic Forecasting for Wireless Network Optimization
Haoye Chai, Shiyuan Zhang, Xiaoqian Qi +2
Mobile traffic forecasting allows operators to anticipate network dynamics and performance in advance, offering substantial potential for enhancing service quality and improving us…
Large-scale Urban Facility Location Selection with Knowledge-informed Reinforcement Learning
Hongyuan Su, Yu Zheng, Jingtao Ding +2
The facility location problem (FLP) is a classical combinatorial optimization challenge aimed at strategically laying out facilities to maximize their accessibility. In this paper,…
Deep Learning with Data Privacy via Residual Perturbation
Wenqi Tao, Huaming Ling, Zuoqiang Shi +1
Protecting data privacy in deep learning (DL) is of crucial importance. Several celebrated privacy notions have been established and used for privacy-preserving DL. However, many e…
Hierarchical Learning and Computing over Space-Ground Integrated Networks
Jingyang Zhu, Yuanming Shi, Yong Zhou +2
Space-ground integrated networks hold great promise for providing global connectivity, particularly in remote areas where large amounts of valuable data are generated by Internet o…
DATTA: Domain Diversity Aware Test-Time Adaptation for Dynamic Domain Shift Data Streams
Chuyang Ye, Dongyan Wei, Zhendong Liu +5
Test-Time Adaptation (TTA) addresses domain shifts between training and testing. However, existing methods assume a homogeneous target domain (e.g., single domain) at any given tim…
FuXi Weather: A data-to-forecast machine learning system for global weather
Xiuyu Sun, Xiaohui Zhong, Xiaoze Xu +8
Weather forecasting traditionally relies on numerical weather prediction (NWP) systems that integrates global observational systems, data assimilation (DA), and forecasting models.…
Representation learning with CGAN for casual inference
Zhaotian Weng, Jianbo Hong, Lan Wang
Conditional Generative Adversarial Nets (CGAN) is often used to improve conditional image generation performance. However, there is little research on Representation learning with…
Towards Lightweight Graph Neural Network Search with Curriculum Graph Sparsification
Beini Xie, Heng Chang, Ziwei Zhang +5
Graph Neural Architecture Search (GNAS) has achieved superior performance on various graph-structured tasks. However, existing GNAS studies overlook the applications of GNAS in res…
Kolmogorov Arnold Informed neural network: A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov Arnold Networks
Yizheng Wang, Jia Sun, Jinshuai Bai +5
AI for partial differential equations (PDEs) has garnered significant attention, particularly with the emergence of Physics-informed neural networks (PINNs). The recent advent of K…
Interpretable Data Fusion for Distributed Learning: A Representative Approach via Gradient Matching
Mengchen Fan, Baocheng Geng, Keren Li +2
This paper introduces a representative-based approach for distributed learning that transforms multiple raw data points into a virtual representation. Unlike traditional distribute…
Guidance Design for Escape Flight Vehicle Using Evolution Strategy Enhanced Deep Reinforcement Learning
Xiao Hu, Tianshu Wang, Min Gong +1
Guidance commands of flight vehicles are a series of data sets with fixed time intervals, thus guidance design constitutes a sequential decision problem and satisfies the basic con…
Deep Learning for Detecting and Early Predicting Chronic Obstructive Pulmonary Disease from Spirogram Time Series
Shuhao Mei, Xin Li, Yuxi Zhou +9
Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow obstruction. Current diagnostic methods primarily rely on identifying prominent fe…
Revisiting Neural Networks for Continual Learning: An Architectural Perspective
Aojun Lu, Tao Feng, Hangjie Yuan +2
Efforts to overcome catastrophic forgetting have primarily centered around developing more effective Continual Learning (CL) methods. In contrast, less attention was devoted to ana…
Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study
Zechun Niu, Zhilin Zhang, Jiaxin Mao +2
Counterfactual learning to rank (CLTR) has attracted extensive attention in the IR community for its ability to leverage massive logged user interaction data to train ranking model…
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide
Sunwoo Kim, Soo Yong Lee, Yue Gao +3
Higher-order interactions (HOIs) are ubiquitous in real-world complex systems and applications. Investigation of deep learning for HOIs, thus, has become a valuable agenda for the…
Energy-Based Models with Applications to Speech and Language Processing
Zhijian Ou
Energy-Based Models (EBMs) are an important class of probabilistic models, also known as random fields and undirected graphical models. EBMs are un-normalized and thus radically di…
Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission
Ziwen Wang, Jin Wee Lee, Tanujit Chakraborty +5
Survival analysis is essential for studying time-to-event outcomes and providing a dynamic understanding of the probability of an event occurring over time. Various survival analys…
Advancing Additive Manufacturing through Deep Learning: A Comprehensive Review of Current Progress and Future Challenges
Amirul Islam Saimon, Emmanuel Yangue, Xiaowei Yue +2
This paper presents the first comprehensive literature review of deep learning (DL) applications in additive manufacturing (AM). It addresses the need for a thorough analysis in th…