开课单位--伦敦大学学院
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Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search[使用基于样本的搜索进行高效的贝叶斯自适应强化学习]
Arthur Guez(伦敦大学学院) Bayesian model-based reinforcement learning is a formally elegant approach to learning optimal behaviour under model uncertainty, trading off explora...
热度:38
Arthur Guez(伦敦大学学院) Bayesian model-based reinforcement learning is a formally elegant approach to learning optimal behaviour under model uncertainty, trading off explora...
热度:38
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Probabilistic Integration for Uncertainty Quantification in Differential Equation Models[微分方程模型不确定性量化的概率积分法 ]
Ben Calderhead(伦敦大学学院) In this talk I discuss recent joint work with Oksana Chkrebtii, Prof. Dave Campbell and Prof. Mark Girolami, in which we develop a probabilistic forma...
热度:69
Ben Calderhead(伦敦大学学院) In this talk I discuss recent joint work with Oksana Chkrebtii, Prof. Dave Campbell and Prof. Mark Girolami, in which we develop a probabilistic forma...
热度:69
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Various Formulations for Learning the Kernel and Structured Sparsity[学习内核和结构稀疏性的各种公式 ]
Massimiliano Pontil(伦敦大学学院) I will review an approach to learning the kernel, which consists in minimizing a convex objective function over a prescribed set of kernel matrices. I...
热度:37
Massimiliano Pontil(伦敦大学学院) I will review an approach to learning the kernel, which consists in minimizing a convex objective function over a prescribed set of kernel matrices. I...
热度:37
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Multiple Gaussian Process Models[多高斯过程模型]
Cedric Archambeau(伦敦大学学院) We consider a Gaussian process formulation of the multiple kernel learning problem. The goal is to select the convex combination of kernel matrices th...
热度:98
Cedric Archambeau(伦敦大学学院) We consider a Gaussian process formulation of the multiple kernel learning problem. The goal is to select the convex combination of kernel matrices th...
热度:98
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Spectral learning of linear dynamics from generalisedlinear observations with application to neural population data[线性动力学的谱学从广义线性观测到应用于神经种群数据]
Lars Buesing(伦敦大学学院) Latent linear dynamical systems with generalised-linear observation models arise in a variety of applications, for example when modelling the spiking ...
热度:53
Lars Buesing(伦敦大学学院) Latent linear dynamical systems with generalised-linear observation models arise in a variety of applications, for example when modelling the spiking ...
热度:53
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A Family of Penalty Functions for Structured Sparsity[一组用于构造稀疏性的惩罚函数]
Jean Morales(伦敦大学学院) We study the problem of learning a sparse linear regression vector under additional conditions on the structure of its sparsity pattern. We present a ...
热度:81
Jean Morales(伦敦大学学院) We study the problem of learning a sparse linear regression vector under additional conditions on the structure of its sparsity pattern. We present a ...
热度:81
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Measures of Statistical Dependence[统计依赖度量]
Arthur Gretton(伦敦大学学院) A number of important problems in signal processing depend on measures of statistical dependence. For instance, this dependence is minimised in the co...
热度:118
Arthur Gretton(伦敦大学学院) A number of important problems in signal processing depend on measures of statistical dependence. For instance, this dependence is minimised in the co...
热度:118
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What Harm Does Pathological Synchronization in Parkinson's Disease Do?[帕金森病的病理同步有什么危害?]
Peter Brown(伦敦大学学院) Like tuning in a station on the FM band of a radio, neuroscientists can detect the particular frequencies of our brains in action. And just as on the ...
热度:60
Peter Brown(伦敦大学学院) Like tuning in a station on the FM band of a radio, neuroscientists can detect the particular frequencies of our brains in action. And just as on the ...
热度:60
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Online Similarity Prediction of Networked Data from Known and Unknown Graphs[已知图和未知图的网络数据的在线相似度预测]
Mark Herbster(伦敦大学学院) We consider online similarity prediction problems over networked data. We begin by relating this task to the more standard class prediction problem, s...
热度:29
Mark Herbster(伦敦大学学院) We consider online similarity prediction problems over networked data. We begin by relating this task to the more standard class prediction problem, s...
热度:29
![](functions/showpic.php?filename=2019051609270472.jpg)
Modeling Natural Sounds with Modulation Cascade Processes[用调制级联过程建模自然声音]
Richard Turner(伦敦大学学院) Auditory scene analysis is extremely challenging. One approach, perhaps that adopted by the brain, is to shape useful representations of sounds on pri...
热度:88
Richard Turner(伦敦大学学院) Auditory scene analysis is extremely challenging. One approach, perhaps that adopted by the brain, is to shape useful representations of sounds on pri...
热度:88