开课单位--加州大学伯克利分校
61
62
63
64
65
66
67
![](functions/showpic.php?filename=2019042109382642.png)
Sequence Kernels for Predicting Protein Essentiality[用于预测蛋白质必需性的序列核]
Ameet Talwalkar(加州大学伯克利分校) The problem of identifying the minimal gene set required to sustain life is of crucial importance in understanding cellular mechanisms and designing t...
热度:54
Ameet Talwalkar(加州大学伯克利分校) The problem of identifying the minimal gene set required to sustain life is of crucial importance in understanding cellular mechanisms and designing t...
热度:54
![](functions/showpic.php?filename=2019042108114839.png)
An RKHS for Multi-View Learning and Manifold Co-Regularization[用于多视图学习和流形协调的RKHS]
David S. Rosenberg(加州大学伯克利分校) Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing ...
热度:42
David S. Rosenberg(加州大学伯克利分校) Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing ...
热度:42
![](functions/showpic.php?filename=2019041709182541.png)
Learning All Optimal Policies with Multiple Criteria[学习具有多个标准的所有最优策略]
Leon Barrett(加州大学伯克利分校) We describe an algorithm for learning in the presence of multiple criteria. Our technique generalizes previous approaches in that it can learn optimal...
热度:78
Leon Barrett(加州大学伯克利分校) We describe an algorithm for learning in the presence of multiple criteria. Our technique generalizes previous approaches in that it can learn optimal...
热度:78
![](functions/showpic.php?filename=2019041603362882.png)
Deducing Local Influence Neighbourhoods With Application to Edge-Preserving Image Denoising[推导局部影响邻域及其在边缘保持图像去噪中的应用]
Ashish Raj(加州大学伯克利分校) Traditional image models enforce global smoothness, and more recently Markovian Field priors. Unfortunately global models are inadequate to represent ...
热度:25
Ashish Raj(加州大学伯克利分校) Traditional image models enforce global smoothness, and more recently Markovian Field priors. Unfortunately global models are inadequate to represent ...
热度:25
![](functions/showpic.php?filename=2019032708210376.png)
Capacity Control for Partially Ordered Feature Sets[部分排序特征集的容量控制]
Ulrich Rückert(加州大学伯克利分校) Partially ordered feature sets appear naturally in classification settings with structured instances. For example, when the instances are graphs and t...
热度:43
Ulrich Rückert(加州大学伯克利分校) Partially ordered feature sets appear naturally in classification settings with structured instances. For example, when the instances are graphs and t...
热度:43
![](functions/showpic.php?filename=2019030608371289.png)
Does an efficient calibrated forecasting strategy exist?[是否存在有效的校准预测策略?]
Jacob Abernethy(加州大学伯克利分校) We recall two previously-proposed notions of asymptotic calibration for a forecaster making a sequence of probability predictions. We note that the ex...
热度:68
Jacob Abernethy(加州大学伯克利分校) We recall two previously-proposed notions of asymptotic calibration for a forecaster making a sequence of probability predictions. We note that the ex...
热度:68
![](functions/showpic.php?filename=2021021001475365.jpg)
Cognitive science for machine learning 3: Models and theories in cognitive science[机器学习的认知科学3:认知科学中的模型与理论]
Tom Griffiths(加州大学伯克利分校)
热度:19
Tom Griffiths(加州大学伯克利分校)
热度:19