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“展宏图，觅灵机”图灵班系列讲座第3讲：樊文飞院士解读“Big Graphs”（图）
图灵班 第3讲 樊文飞 Big Graphs 数据库
2023/11/30
2023年2月22日，中国科学院外籍院士、英国皇家学会院士樊文飞教授做客南科大。樊院士主要从事数据库理论与系统方面的研究，此次围绕“大规模图数据（Big Graphs）”主题，与在场师生分享了他对此方面的深刻见解。会议由计算机科学与工程系主任姚新教授主持，副主任王琦副教授、计算机系部分教师、图灵班各年级学生以及部分研究生到场聆听了报告。
Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs（图）
GPU 流水线 大型图形 深度学习
2023/6/20
Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial transactions, traffic, energy gri...
PRIVATE GRAPHS – ACCESS RIGHTS ON GRAPHS FOR SEAMLESS NAVIGATION
Geospatial Data Security Access Control Navigation Graph Graph Segmentation
2016/11/8
After the success of GNSS (Global Navigational Satellite Systems) and navigation services for public streets, indoor seems to be the next big development in navigational services, relying on RTLS – Re...
EFFICIENT AND ACCURATE INDOOR LOCALIZATION USING LANDMARK GRAPHS
Indoor Localization Landmark Graph Dead Reckoning
2016/7/8
Indoor localization is important for a variety of applications such as location-based services, mobile social networks, and emergency response. Fusing spatial information is an effective way to achiev...
Partial Online Cycle Elimination in Inclusion Constraint Graphs
Partial Online Cycle Elimination Inclusion Constraint Graphs
2016/5/24
Many program analyses are naturally formulated and implemented using inclusion constraints. We present new results on the scalable implementation of such analyses based on two insights: rst, that onl...
Projection Merging: Reducing Redundancies in Inclusion Constraint Graphs
Projection Merging Reducing Redundancies Inclusion Constraint Graphs
2016/5/24
Inclusion-based program analyses are implemented by adding new edges to directed graphs. In most analyses, there are many di erent ways to add a transitive edge between two nodes, namely through each ...
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs
Top-k Selection Multi-Armed Bandits Hidden Bipartite Graphs
2016/1/22
This paper discusses how to efficiently choose from n unknown distributions the k ones whose means are the greatest by a certain metric, up to a small relative error.We study the topic under two stand...
The dynamics of message passing on dense graphs, with applications to compressed sensing
Mohsen Bayatil Andrea Montanari
2015/8/20
‘Approximate message passing’ algorithms proved to be extremely effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive numerical experiments furthe...
Network lasso: Clustering and optimization in large graphs
Convex Optimization ADMM Network Lasso
2015/8/7
Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimiza...
Optimal Controller Synthesis for Decentralized Systems over Graphs via Spectral Factorization
Decentralized Systems Controller Synthesis
2015/6/19
In this paper, controller synthesis algorithms are developed for decentralized control problems. The distributed systems considered here are represented by graphs, which impose sparsity constraints on...
Basis Construction and Utilization for Markov Decision Processes Using Graphs
Markov decision process Reinforcement learning Representation discovery
2014/12/18
The ease or difficulty in solving a problemstrongly depends on the way it is represented. For example, consider the task of multiplying the numbers 12 and 24. Now imagine multiplying XII and XXIV. Bot...
Scheduling Heuristics for Maximizing the Output Quality of IRIS Task Graphs in Multiprocessor Environment with Time and Energy Bounds
precedence constraints computational load cost functions reward service dynamic voltage scaling
2014/12/8
Embedded real time applications are often subject to time and energy constraints. Real time applications are usually characterized by logically separable set of tasks with precedence constraints. The ...
HYPERSPECTRAL DATA CLASSIFICATION USING FACTOR GRAPHS
Hyper spectral Classification Training Reference Data
2014/4/29
Accurate classification of hyperspectral data is still a competitive task and new classification methods are developed to achieve desired tasks of hyperspectral data use. The objective of this paper i...
Spectra of sparse regular graphs with loops
sparse regular graphs loops Statistical Mechanics
2011/10/9
Abstract: We derive exact equations that determine the spectra of undirected and directed sparsely connected regular graphs containing loops of arbitrary length. The implications of our results to the...
Signed (b,k)-Edge Covers in Graphs
Signed Star Dominating Function Signed Star Domination Number Signed -edge Cover Signed -edge Cover Number
2013/1/28
Let be a simple graph with vertex set and edge set . Let have at least vertices of degree at least , where and are positive integers. A function is said to be a signed -edge cover of if for at least v...