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Domain Adaptation Workshop: Theory and Application
Despite the recent advances in domain adaptation, many of the most successful practical achievements in domain adaptation have not been robust, in part because they lack formal assumptions about when they could perform well. At the same time, some of the most influential theoretical work guarantees near optimal performance in new domains, but under assumptions that may not hold in practice.
Our workshop will bridge theory and practice in the following ways:
1.We will have one applied and two theoretical invited talks.
2.We will advertise the workshop to both the applied and theoretical communities.
3.We will have discussion sessions whose aim emphasizes both the formal assumptions underlying successful practical algorithms and new algorithms based on theoretical foundations.
Workshop attendees should come away with an understanding of the domain adaptation problem, how it appears in practical applications and existing theoretical guarantees that can be provided in this more general setting. More importantly, attendees will be exposed to the important open problems of the field, which will encourage new collaborations and results.
Machine Learning in Computational Biology (MLCB) 2011
A workshop at the annual Conference on Neural Information Processing Systems (NIPS 2011) @ Sierra Nevada, Spain, December 17, 2011.
NIPS 2011 Workshop on Integrating Language and Vision
A growing number of researchers in computer vision have started to explore how language accompanying images and video can be used to aid interpretation and retrieval, as well as train object and activity recognizers. Simultaneously, an increasing number of computational linguists have begun to investigate how visual information can be used to aid language learning and interpretation, and to ground the meaning of words and sentences in perception. However, there has been very little direct interaction between researchers in these two distinct disciplines. Consequently, researchers in each area have a limited understanding of the methods in the other area, and do not optimally exploit the latest ideas and techniques from both disciplines when developing systems that integrate language and vision. The goal of this workshop is to bring together researchers in both computer vision and natural-language processing (NLP) to interact, collaborate, and discuss issues and future directions in integrating language and vision.
Traditional machine learning for both computer vision and NLP requires manually annotating images, video, text, or speech with detailed labels, parse-trees, segmentations, etc. Methods that integrate language and vision hold the promise of greatly reducing such manual supervision by using naturally co-occurring text and images/video to mutually supervise each other.
There is a wide range of important real-world applications that require integrating vision and language, including but not limited to: image and video retrieval, human-robot interaction, medical image processing, human-computer interaction in virtual worlds, and computer graphics generation.
Copulas in Machine Learning Workshop 2011
From high-throughput biology and astronomy to voice analysis and medical diagnosis, a wide variety of complex domains are inherently continuous and high dimensional. The statistical framework of copulas offers a flexible tool for modeling highly non-linear multivariate distributions for continuous data. Copulas are a theoretically and practically important tool from statistics that explicitly allow one to separate the dependency structure between random variables from their marginal distributions. Although bivariate copulas are a widely used tool in finance, and have even been famously accused of "bringing the world financial system to its knees" (Wired Magazine, Feb. 23, 2009), the use of copulas for high dimensional data is in its infancy.
While studied in statistics for many years, copulas have only recently been noticed by a number of machine learning researchers, with this "new" tool appearing in the recent leading machine learning conferences (ICML, UAI and NIPS). The goal of this workshop is to promote the further understanding and development of copulas for the kinds of complex modeling tasks that are the focus of machine learning. Specifically, the goals of the workshop are to:
* draw the attention of machine learning researchers to the
important framework of copulas
* provide a theoretical and practical introduction to copulas
* identify promising research problems in machine learning that
could exploit copulas
* bring together researchers from the statistics and machine learning communities working in this area.
The target audience includes leading researchers from academia and industry, with the aim of facilitating cross fertilization between
1st Lisbon Machine Learning School
LxMLS 2011 will take place July 20-25 (*) at Instituto Superior Tecnico, a leading Engineering and Science school in Portugal. It is organized jointly by IST, the Instituto de Telecomunicacoes and the Spoken Language Systems Lab - L2F of INESC-ID. In its debut year, the topic of the school is Learning for the Web. The school will cover a range of machine learning (ML) Topics, from theory to practice, that are important in solving natural language processing (NLP) problems that arise in the analysis and use of Web data.
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
The WASPAA meeting is a traditional event sponsored by the Audio and Acoustic Signal Processing Committee of the IEEE Signal Processing Society. The first WASPAA meeting was convened in 1986 and since 1989 it has been held every other year. This two-and-a-half day workshop is devoted to reviewing the current state of the art as well as recent advances in signal processing with emphasis on its applications to audio and acoustics. It brings together researchers and practitioners from universities and industry.
Venture Shift New York Webcast
The new era of venture investing. The questions to explore are: How do these developments change the VC game and capital-formation process and exit dynamics? How are the rise of angels, super angels, incubators changing the stakes across the board? Are 10x returns elusive? How are secondary markets adding value? This event is ideal for entrepreneurs seeking to understand the new world order of venture financing from start to finish. Super angels and angels and venture capitalists should also join the event to mingle and connect with fellow investors shaping the new era of venture investing.
Sixth Annual Machine Learning Symposium
The Machine Learning Discussion Group at the New York Academy of Sciences holds an annual symposium each fall to discuss advanced research related to such topics. The aim of this series is to continue to build a community of leading scientists in machine learning from the New York City area's academic, government, and industrial institutions by convening and promoting the exchange of ideas in a neutral setting. Top scientists in both applied and theoretical machine learning are invited to present their research.