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Optimization for Machine Learning
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessi...
İnternational Research in Engineering Sciences III
İnternational Research in Engineering Sciences III
Learning Machine Translation
How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.
Advances in Information Retrieval
The annual colloquium on information retrieval research provides an opportunity for both new and established researchers to present papers describing work in progress or ?nal results. This colloquium was established by the BCS IRSG(B- tish Computer Society Information Retrieval Specialist Group), and named the Annual Colloquium on Information Retrieval Research. Recently, the location of the colloquium has alternated between the United Kingdom and continental Europe. To re?ect the growing European orientation of the event, the colloquium was renamed “European Annual Colloquium on Information Retrieval Research” from 2001. Since the inception of the colloquium in 1979 the event has been h...
Translation in Transition
Extraordinary advances in machine translation over the last three quarters of a century have profoundly affected many aspects of the translation profession. The widespread integration of adaptive “artificially intelligent” technologies has radically changed the way many translators think and work. In turn, groundbreaking empirical research has yielded new perspectives on the cognitive basis of the human translation process. Translation is in the throes of radical transition on both professional and academic levels. The game-changing introduction of neural machine translation engines almost a decade ago accelerated these transitions. This volume takes stock of the depth and breadth of resulting developments, highlighting the emerging rivalry of human and machine intelligence. The gathering and analysis of big data is a common thread that has given access to new insights in widely divergent areas, from literary translation to movie subtitling to consecutive interpreting to development of flexible and powerful new cognitive models of translation.
Encyclopedia of Machine Learning
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Information and Communication Technologies in Tourism 1999
During the last couple of years we learned that infonnation and communication technologies have to be seen as key factors for the success in various industries. Especially in tourism it became evident, that missing the developments in this sector could not only be fatal for the unfolding of the businesses, but also unrenouncable in order to withstand in competition. The objective of ENTER is to show the chance that infonnation technology offers for all participants in the touristic competition to act successfully in permanently changing infonnation environments. It reflects the important role of infonnation technologies in this field. Within the last six years ENTER united various experts - practitioners as well as researchers - to exchange their experiences, ideas and visions in the sector of tourism and infonnation technology. The conferences scope is to provide an international platfonn to discuss the topical situation and future trends, and the possibilities to shape the own strategies. The various points of view of all the participants in workshops, reports and discussions always lead to most interesting perceptions.
Advances in Neural Information Processing Systems 16
Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.
Practical Applications of Sparse Modeling
"Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional data sets. This collection describes key approaches in sparse modeling, focusing on its applications in such fields as neuroscience, computational biology, and computer vision. Sparse modeling methods can improve the interpretability of predictive models and aid efficient recovery of high-dimensional unobserved signals from a limited number of measurements. Yet despite significant advances in the field, a number of open issues remain when sparse modeling meets real-life applications. The book discusses a range of practical applications and state-of-the-art approaches for tackling the challenges presented by these applications. Topics considered include the choice of method in genomics applications; analysis of protein mass-spectrometry data; the stability of sparse models in brain imaging applications; sequential testing approaches; algorithmic aspects of sparse recovery; and learning sparse latent models"--Jacket.
Eyetracking and Applied Linguistics
Eyetracking has become a powerful tool in scientific research and has finally found its way into disciplines such as applied linguistics and translation studies, paving the way for new insights and challenges in these fields. The aim of the first International Conference on Eyetracking and Applied Linguistics (ICEAL) was to bring together researchers who use eyetracking to empirically answer their research questions. It was intended to bridge the gaps between applied linguistics, translation studies, cognitive science and computational linguistics on the one hand and to further encourage innovative research methodologies and data triangulation on the other hand. These challenges are also addressed in this proceedings volume: While the studies described in the volume deal with a wide range of topics, they all agree on eyetracking as an appropriate methodology in empirical research.
