图 书 馆开课单位--多伦多大学
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21Dropout: A simple and effective way to improve neural networks[辍学：改进神经网络的一种简单有效的方法]
Geoffrey E. Hinton(多伦多大学) In a large feedforward neural network, overfitting can be greatly reduced by randomly omitting half of the hidden units on each training case. This pr...
热度：51
Geoffrey E. Hinton(多伦多大学) In a large feedforward neural network, overfitting can be greatly reduced by randomly omitting half of the hidden units on each training case. This pr...
热度：51
22Incorporating Structure in Deep Learning[深度学习中的整合结构]
Raquel Urtasun(多伦多大学) Deep learning algorithms attempt to model high-level abstractions of the data using architectures composed of multiple non-linear transformations. A m...
热度：67
Raquel Urtasun(多伦多大学) Deep learning algorithms attempt to model high-level abstractions of the data using architectures composed of multiple non-linear transformations. A m...
热度：67
23Deep Learning[深度学习]
Ruslan Salakhutdinov(多伦多大学) Building intelligent systems that are capable of extracting high-level representations from high-dimensional sensory data lies at the core of solving ...
热度：25
Ruslan Salakhutdinov(多伦多大学) Building intelligent systems that are capable of extracting high-level representations from high-dimensional sensory data lies at the core of solving ...
热度：25
24Playing Atari with Deep Reinforcement Learning[在深层强化学习中玩雅达利]
Volodymyr Mnih(多伦多大学) We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learn...
热度：37
Volodymyr Mnih(多伦多大学) We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learn...
热度：37
25Automatically labeled data generation for classification of reputation defence strategies[声誉防御策略分类的自动标记数据生成]
Nona Naderi(多伦多大学) Reputation defence is a form of persuasive tactic that is used in various social settings especially in political situations. Detection of reputation ...
热度：27
Nona Naderi(多伦多大学) Reputation defence is a form of persuasive tactic that is used in various social settings especially in political situations. Detection of reputation ...
热度：27
26Characterization of pancreatic alpha-cell physiology in pancreatic slices[胰腺切片胰岛α细胞生理特性]
Ya-Chi Huang(多伦多大学) Characterization of pancreatic alpha-cell physiology in pancreatic slices
热度：229
Ya-Chi Huang(多伦多大学) Characterization of pancreatic alpha-cell physiology in pancreatic slices
热度：229
27Dropout: A simple and effective way to improve neural networks[辍学：改进神经网络的一种简单有效的方法]
Geoffrey E. Hinton(多伦多大学) In a large feedforward neural network, overfitting can be greatly reduced by randomly omitting half of the hidden units on each training case. This pr...
热度：18
Geoffrey E. Hinton(多伦多大学) In a large feedforward neural network, overfitting can be greatly reduced by randomly omitting half of the hidden units on each training case. This pr...
热度：18
28Gaussian Processes for Monocular 3D People tracking[高斯过程单眼3D的人跟踪]
Raquel Urtasun(多伦多大学) We advocate the use of Gaussian Processes (GPs) to learn prior models of human pose and motion for 3D people tracking. The Gaussian Process Latent var...
热度：50
Raquel Urtasun(多伦多大学) We advocate the use of Gaussian Processes (GPs) to learn prior models of human pose and motion for 3D people tracking. The Gaussian Process Latent var...
热度：50
29Learning Human Pose and Motion Models for Animation[学习人体姿势和运动模型的动画]
Aaron Hertzmann(多伦多大学) Computer animation is an extraordinarily labor-intensive process; obtaining high-quality motion models could make the process faster and easier. I wil...
热度：57
Aaron Hertzmann(多伦多大学) Computer animation is an extraordinarily labor-intensive process; obtaining high-quality motion models could make the process faster and easier. I wil...
热度：57
30Web Service Composition via Generic Procedures & Customizing User Preferences[Web服务组合通过通用程序]
Shirin Sohrabi Araghi(多伦多大学) Research 7: Web Service Composition via Generic Procedures & Customizing User Preferences.
热度：62
Shirin Sohrabi Araghi(多伦多大学) Research 7: Web Service Composition via Generic Procedures & Customizing User Preferences.
热度：62