Although clustering data into mutually exclusive partitions has been an extremely successful approach to unsupervised learning, there are many situations in which a richer model is needed to fully represent the data. This is the case in problems where data points actually simultaneously belong to multiple, overlapping clusters. For example a particular gene may have several functions, therefore...

We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). We deal with the situation arising when wanting to learn sdfa from unrepeated examples. This is intended to model the situation where the data is not generated automatically, but in an order dependent of its probability...

Expert combination is a classic strategy that has been widely used in various problem solving tasks. A team of individuals with diverse and complementary skills tackle a task jointly such that a performance better than any single individual can make is achieved via integrating the strengths of individuals. Started from the late 1980’ in the handwritten character recognition literature, studies ...

Window-based matching such as normalized cross-correlation (NCC) can reliably estimate depth even when the constant brightness assumption is violated in stereo due to imaging noise or different camera gains. However, fixed window methods tend to have poor performance at depth discontinuities and in low-texture regions. In this paper, we describes a novel learning-based algorithm, for stereo mat...

In the last three lectures we have been discussing the online learning algorithms where we receive the instance x and then its label y for t = 1, ..., T . Specifically in the last lecture we talked about online learning from experts and online prediction. We saw many algorithms like Halving algorithm, Weighted Majority (WM) algorithm and lastly Weighted Majority Continuous (WMC) algorithm. We a...

the quality of learning is one of the basic elements in every society to reach achievements. this subject has more importance on e-learning. accordingly, the present study explains the affecting factors on e-learning programs’ effectiveness. regarding the aims, the present research is descriptive and regarding the application is practical. data collection method is research made questioner. in ...

many previous studies used leader - member exchange to explain the quality relationship between employees and supervisors. however, in previous studies, the mechanism of this theory in creativity is not so clear. thus, this study defines the role of leaders in creating a culture of organizational learning using normative approach to examine the relationship between communication quality leader ...

This paper presents a method for one-shot learning of dexterous grasps, and grasp generation for novel objects. A model of each grasp type is learned from a single kinesthetic demonstration, and several types are taught. These models are used to select and generate grasps for unfamiliar objects. Both the learning and generation stages use an incomplete point cloud from a depth camera – no prior...

Bayesian network modeling by domain experts is still mainly a process of trial and error. The structure of the graph and the specification of the conditional probability tables (ePTs) are in practice often fiddled until a desired model behavior is obtained. We describe a development tool in which graph specification and ePT modeling are fully separated. Furthermore, the tuning of ePTs is handle...