Search Results - CCS Concepts: • Theory of computation → Theory and algorithms for application domains

Efficient Path Generation with Reduced Coordinates by Chen, Renjie, Gotsman, Craig, Hormann, Kai

“…Path generation is an important problem in many fields, especially robotics. One way to create a path between a source point z and a target point y inside a complex planar domain Ω is to define a non…”
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Topology-aware GPU scheduling for learning workloads in cloud environments by Amaral, Marcelo, Polo, Jordà, Carrera, David, Seelam, Seetharami, Steinder, Malgorzata

“…Recent advances in hardware, such as systems with multiple GPUs and their availability in the cloud, are enabling deep learning in various domains including health care, autonomous vehicles, and Internet of Things…”
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Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation by Chen, Letian, Paleja, Rohan, Ghuy, Muyleng, Gombolay, Matthew

“…Reinforcement learning (RL) has achieved tremendous success as a general framework for learning how to make decisions. However, this success relies on the…”
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Early Detection of Problem Gambling based on Behavioral Changes using Shapelets by Suzuki, Hiroko, Nakamura, Ryoko, Inagaki, Aozora, Watanabe, Isamu, Takagi, Tomohiro

“…Recent years have seen strides achieved in the field of behavior analysis by using online gambling data. However, studies on time-series behavioral changes…”
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Multi-Agent Pursuit-Evasion Game Based on Organizational Architecture by Souidi, Mohammed El Habib, Siam, Abderrahim, Pei, Zhaoyi, Piao, Songhao

“… (Yet Another Multi Agent Model). Specifically, we have used the concepts Agent, Role, Task, and Skill, proposed in this model to develop a coalition formation algorithm to allow the optimal task sharing…”
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A Simple Density with Distance Based Initial Seed Selection Technique for K Means Algorithm by Syed Azimuddin, Sajidha, Desikan, Kalyani

“…Open issues with respect to K means algorithm are identifying the number of clusters, initial seed concept selection, clustering tendency, handling empty clusters, identifying outliers etc…”
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Graph Deep Learning: Methods and Applications by Zhang, Muhan

“…The past few years have seen the growing prevalence of deep neural networks on various application domains including image processing, computer vision, speech recognition, machine translation, self…”
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