图 书 馆开课单位--伦敦大学学院
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131Introduction to the Workshop[研讨会简介]
David R. Hardoon(伦敦大学学院) Until recently, the issue of musical representation had focused primarily on symbolic notation of musical information and structure, and on the repres...
热度：38
David R. Hardoon(伦敦大学学院) Until recently, the issue of musical representation had focused primarily on symbolic notation of musical information and structure, and on the repres...
热度：38
132Linear Programming Boosting for Classification of Musical Genre[音乐流派分类的线性规划推进]
Tom Diethe(伦敦大学学院) Classification of musical genre from raw audio files is a fairly well researched area of music research, and as such provides a good starting point fo...
热度：65
Tom Diethe(伦敦大学学院) Classification of musical genre from raw audio files is a fairly well researched area of music research, and as such provides a good starting point fo...
热度：65
133Kernel Learning for Novelty Detection[新颖性检测的核学习 ]
John Shawe-Taylor(伦敦大学学院) We consider kernel learning for one-class Support Vector Machines. We consider a mix of 2- and 1-norms of the individual weight vector norms allowing...
热度：35
John Shawe-Taylor(伦敦大学学院) We consider kernel learning for one-class Support Vector Machines. We consider a mix of 2- and 1-norms of the individual weight vector norms allowing...
热度：35
134Data variability could be your friend[数据变化可能是你的朋友]
Martino Barenco(伦敦大学学院 ) Deterministic modeling, in the form of ordinary differential equations (ODE), is the dominant paradigm in systems biology. This stems partially from t...
热度：84
Martino Barenco(伦敦大学学院 ) Deterministic modeling, in the form of ordinary differential equations (ODE), is the dominant paradigm in systems biology. This stems partially from t...
热度：84
135A Stochastic Memoizer for Sequence Data[序列数据的随机存储器]
Frank Wood(伦敦大学学院) We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single traini...
热度：28
Frank Wood(伦敦大学学院) We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single traini...
热度：28
136Sample-Based Learning and Search with Permanent and Transient Memories[基于样本的学习的搜索算法是永久学习和瞬态记忆分离]
David Silver(伦敦大学学院) We present a reinforcement learning architecture, Dyna-2, that encompasses both sample-based learning and sample-based search, and that generalises ac...
热度：57
David Silver(伦敦大学学院) We present a reinforcement learning architecture, Dyna-2, that encompasses both sample-based learning and sample-based search, and that generalises ac...
热度：57
137Free energy and active inference[自由能量和主动推断]
Karl Friston(伦敦大学学院) How much about our interactions with - and experience of - our world can be deduced from basic principles? This talk reviews recent attempts to unders...
热度：47
Karl Friston(伦敦大学学院) How much about our interactions with - and experience of - our world can be deduced from basic principles? This talk reviews recent attempts to unders...
热度：47