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  • CVPR Vision meets Cognition Workshop 2014

    With the emergence of new technologies, including Kinect, Google Glasses, and autonomous driving, Computer Vision is about to play a key role in human daily life. The massive presence of sensors in a wide range of contexts demands an expansion in the scope of image understanding by answering queries beyond "what is where". The missions of this workshop are therefore to (a) identify the key domains in the new scope; (b) recognize the computational challenges in these domains; and (c) provide promising frameworks for solving these challenges.

  • CVPR 2014 Oral Talks

    Videos of CVPR 2014 Oral Presentations

  • CVPR 2014 Video Spotlights

    User generated CVPR 2014 Video Spotlights

  • WritersUA West 2014

    The Conference for Software User Assistance was held in Seattle, WA.

  • NYU Course on Machine Learning and Computational Statistics 2014

    Machine learning is an exciting and fast-moving field at the intersection of computer science, statistics, and optimization with many recent consumer applications (e.g., Microsoft Kinect, Google Translate, Iphone's Siri, digital camera face detection, Netflix recommendations, Google news). Machine learning and computational statistics also play a central role in data science. In this graduate-level class, students will learn about the theoretical foundations of machine learning and computational statistics and how to apply these to solve new problems. This is a required course for the MS in Data Science and should be taken in the first year of study; it is also suitable for MS and Ph.D. students in Computer Science and related fields (see pre-requisites below).

  • NYU Course on Big Data (Spring 2014)

    Big Data requires the storage, organization, and processing of data at a scale and efficiency that go well beyond the capabilities of conventional information technologies. In this course, we will study the state of the art in big data management: we will learn about algorithms, techniques and tools needed to support big data processing. In addition, we will examine real applications that require massive data analysis and how they can be implemented on Big Data platforms. The course will consist of lectures based both on textbook material and scientific papers. It will also include programming assignments that will provide students with hands-on experience on building data-intensive applications using existing Big Data platforms, including Amazon AWS. Besides lectures given by the instructor, we will also have guest lectures by experts in some of the topics we will cover.

  • NYU Course on Deep Learning (Spring 2014)

    This is a graduate course on deep learning, one of the hottest topics in machine learning and AI at the moment. In the last two or three years, Deep learning has revolutionized speech recognition and image recognition. Deep learning is widely deployed by such companies as Google, Facebook, Microsoft, IBM, Baidu, Apple and others for audio/speech, image, video, and natural language processing.

  • LxMLS 2013

    LxMLS 2013 took place July 24-31 at Instituto Superior Técnico, a leading Engineering and Science school in Portugal.

  • FOCS 2013

    The 54th Annual Symposium on Foundations of Computer Science (FOCS 2013), sponsored by the IEEE Computer Society Technical Committee on Mathematical Foundations of Computing, was held in Berkeley, California on October 27–29, 2013 (Sunday through Tuesday).