图 书 馆开课单位--爱丁堡大学
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31Inexact Search Directions in Interior Point Methods for Large Scale Optimization[大规模优化内点法的不精确搜索方向 ]
Jacek Gondzio(爱丁堡大学 ) Interior Point Methods (IPMs) for linear and quadratic optimization have been very successful but occasionally they struggle with excessive memory req...
热度：76
Jacek Gondzio(爱丁堡大学 ) Interior Point Methods (IPMs) for linear and quadratic optimization have been very successful but occasionally they struggle with excessive memory req...
热度：76
32Machine Learning Markets[机器学习市场 ]
Amos Storkey(爱丁堡大学) Prediction markets show considerable promise for developing flexible mechanisms for machine learning. Here, machine learning markets for multivariate ...
热度：38
Amos Storkey(爱丁堡大学) Prediction markets show considerable promise for developing flexible mechanisms for machine learning. Here, machine learning markets for multivariate ...
热度：38
33Multi-Task Learning with Gaussian Processes with Applications to Robot Inverse Dynamics[高斯过程多任务学习及其在机器人逆动力学中的应用 ]
Chris Williams(爱丁堡大学) I will discuss multi-task learning, and a number of ways in which transfer between tasks can take place, mainly in a co-kriging (or Gaussian process) ...
热度：105
Chris Williams(爱丁堡大学) I will discuss multi-task learning, and a number of ways in which transfer between tasks can take place, mainly in a co-kriging (or Gaussian process) ...
热度：105
34Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability[知觉双稳中基于采样的概率推理的神经元适应]
David P Reichert(爱丁堡大学) It has been argued that perceptual multistability reflects probabilistic inference performed by the brain when sensory input is ambiguous. Alternative...
热度：38
David P Reichert(爱丁堡大学) It has been argued that perceptual multistability reflects probabilistic inference performed by the brain when sensory input is ambiguous. Alternative...
热度：38
35The NITE XML Toolkit meets the ICSI Meeting Corpus: import, annotation, and browsing[NITE XML Toolkit符合ICSI会议语料库：导入，注释和浏览]
Jean Carletta(爱丁堡大学) The NITE XML Toolkit (NXT) provides library support for working with multimodal language corpora. We describe work in progress to explore its potentia...
热度：91
Jean Carletta(爱丁堡大学) The NITE XML Toolkit (NXT) provides library support for working with multimodal language corpora. We describe work in progress to explore its potentia...
热度：91
36Inference in hierarchical transcriptional network motifs[分层转录网络图案的推论]
Andrea Ocone(爱丁堡大学) We present a novel inference methodology to reverse engineer the dynamics of transcription factors (TFs) in hierarchical network motifs such as feed-f...
热度：47
Andrea Ocone(爱丁堡大学) We present a novel inference methodology to reverse engineer the dynamics of transcription factors (TFs) in hierarchical network motifs such as feed-f...
热度：47
37The AMI Meeting Corpus: A Pre-Announcement[AMI会议语料库：预先公告]
Jean Carletta(爱丁堡大学) The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. It is being created in the context of a project that i...
热度：339
Jean Carletta(爱丁堡大学) The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. It is being created in the context of a project that i...
热度：339
38Continuous Relaxations for Discrete Hamiltonian Monte Carlo[离散哈密顿蒙特卡罗的连续松弛]
Yichuan Zhang(爱丁堡大学) Continuous relaxations play an important role in discrete optimization, but have not seen much use in approximate probabilistic inference. Here we sho...
热度：184
Yichuan Zhang(爱丁堡大学) Continuous relaxations play an important role in discrete optimization, but have not seen much use in approximate probabilistic inference. Here we sho...
热度：184
39Visual Categorization with Bags of Keypoints[用一袋袋的关键点进行视觉分类 ]
Chris Williams(爱丁堡大学 ) We present a novel method for generic visual categorization: the problem of identifying the object content of natural images while generalizing across...
热度：40
Chris Williams(爱丁堡大学 ) We present a novel method for generic visual categorization: the problem of identifying the object content of natural images while generalizing across...
热度：40
40Using Interior Point Methods for Optimization in Training Very Large Scale Support Vector Machines[利用内点法优化训练超大规模支持向量机]
Jacek Gondzio(爱丁堡大学) In this talk we shall discuss the issues of Interior Point Methods (IPMs) applied to solve optimization problems arising in the context of very large-...
热度：64
Jacek Gondzio(爱丁堡大学) In this talk we shall discuss the issues of Interior Point Methods (IPMs) applied to solve optimization problems arising in the context of very large-...
热度：64