开课单位--卡内基梅隆大学
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Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks[使用递归神经网络对实体、关系和文本进行推理链]
Rajarshi Das(卡内基梅隆大学) Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks
热度:18
Rajarshi Das(卡内基梅隆大学) Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks
热度:18
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Robust Top-k Multiclass SVM for Visual Category Recognition[用于视觉类别识别的鲁棒Top-k多类SVM(支持向量机)]
Xiaojun Chang(卡内基梅隆大学) Classification problems with a large number of classes inevitably involve overlapping or similar classes. In such cases it seems reasonable to allow t...
热度:33
Xiaojun Chang(卡内基梅隆大学) Classification problems with a large number of classes inevitably involve overlapping or similar classes. In such cases it seems reasonable to allow t...
热度:33
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Unsupervised Visual Representation Learning by Context Prediction[基于情境预测的无监督视觉表征学习]
Carl Doersch(卡内基梅隆大学) This work explores the use of spatial context as a source of free and plentiful supervisory signal for training a rich visual representation. Given on...
热度:21
Carl Doersch(卡内基梅隆大学) This work explores the use of spatial context as a source of free and plentiful supervisory signal for training a rich visual representation. Given on...
热度:21
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Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)[可扩展结构化高斯过程的核插值]
Andrew Gordon Wilson(卡内基梅隆大学) We introduce a new structured kernel interpolation (SKI) framework, which generalises and unifies inducing point methods for scalable Gaussian process...
热度:72
Andrew Gordon Wilson(卡内基梅隆大学) We introduce a new structured kernel interpolation (SKI) framework, which generalises and unifies inducing point methods for scalable Gaussian process...
热度:72
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Multi-task and Transfer in RL[RL中的多任务和转移]
Emma Brunskill(卡内基梅隆大学) Multi-task and Transfer in RL
热度:20
Emma Brunskill(卡内基梅隆大学) Multi-task and Transfer in RL
热度:20
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SpotLight: Detecting Anomalies in Streaming Graphs[SpotLight:检测流图中的异常]
Dhivya Eswaran(卡内基梅隆大学) How do we spot interesting events from e-mail or transportation logs? How can we detect port scan or denial of service attacks from IP-IP communicatio...
热度:20
Dhivya Eswaran(卡内基梅隆大学) How do we spot interesting events from e-mail or transportation logs? How can we detect port scan or denial of service attacks from IP-IP communicatio...
热度:20
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Activity Forecasting[活动的预测]
Kris M. Kitani(卡内基梅隆大学) We address the task of inferring the future actions of people from noisy visual input. We denote this task activity forecasting. To achieve accurate a...
热度:31
Kris M. Kitani(卡内基梅隆大学) We address the task of inferring the future actions of people from noisy visual input. We denote this task activity forecasting. To achieve accurate a...
热度:31
![](functions/showpic.php?filename=2022120504541825.png)
Learning, Information Extraction and the Web[学习、信息提取和网络]
Tom Mitchell(卡内基梅隆大学) Learning, Information Extraction and the Web
热度:19
Tom Mitchell(卡内基梅隆大学) Learning, Information Extraction and the Web
热度:19
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Large Scale Scene Matching for Graphics and Vision[用于图形和视觉的大规模场景匹配]
James Hays(卡内基梅隆大学) Large Scale Scene Matching for Graphics and Vision
热度:24
James Hays(卡内基梅隆大学) Large Scale Scene Matching for Graphics and Vision
热度:24