Software Engineer - Machine Learning New York Posted Mar 18, 2016 - Requisition No. 49181 Apply Now Our team is made up of data scientists and software engineers. It's common to see us gathered around a whiteboard solving difficult problems. We develop the machine learning models and infrastructure to support Bloomberg products in the areas of Law, Government and New Energy Finance. We extract knowledge from millions of legal documents and use it to build intelligent models with information retrieval, machine learning and natural language processing. This enables our customers to get the right answers - fast.

Object queries are essential in information seeking and decision making in vast areas of applications. However, a query may involve complex conditions on objects and sets, which can be arbitrarily nested and aliased. The objects and sets involved as well as the demand---the given parameter values of interest---can change arbitrarily. How to implement object queries efficiently under all possible updates, and furthermore to provide complexity guarantees? This paper describes an automatic method. The method allows powerful queries to be written completely declaratively. It transforms demand as well as all objects and sets into relations. Most importantly, it defines invariants for not only the query results, but also all auxiliary values about the objects and sets involved, including those for propagating demand, and incrementally maintains all of them. Implementation and experiments with problems from a variety of application areas, including distributed algorithms and probabilistic queries, confirm the analyzed complexities, trade-offs, and significant improvements over prior work.

SummaryCMIS and Apache Chemistry in Action is a comprehensive guide to the CMIS standard and related ECM concepts, written by th...ries Building mobile apps with CMIS PART 3 ADVANCED TOPICS CMIS bindings Security and control Performance Building a CMIS server This is the official OOPic (object oriented embedded microcontroller) manual endorsed by the largest manufacturer of OOPics and ...Pic microcontroller, sample code you can incorporate and customize for your projects, as well as special OOPic-related software. Remarkable progress in eye-tracking technologies opened the way to design novel attention-based intelligent user interfaces, and...n human attentional behaviors and face-to-face communication which are essential in designing gaze aware interactive interfaces. Opening with a detailed review of existing techniques for selective encryption, this text then examines algorithms that combine ...heme with enhanced security features; presents an encryption scheme for image and video data based on chaotic arithmetic coding. This book and software package presents a unified approach for doing mathematical statistics with Mathematica. Create your own natural language training corpus for machine learning.

Lately in the tech world, everything has been revolving around artificial intelligence and machine learning. If you've been interested in learning more about machine learning and getting in on it as well, now you can. Thanks to this fantastic bundle that we have available on the Android Headlines Store. This bundle features 10 courses, over 400 lessons and is discounted by 94% right now. Included in the bundle is Quant Trading Using Machine Learning, Learn by Example: Statistics and Data Science in R, Learn by Example: Hadoop & MapReduce for Big Data Problems, Byte Size Chunks: Java Object-Oriented Programming & Design, An Introduction to Machine Learning & NLP in Python, Byte-Sized-Chunks: Twitter Sentiment Analysis (In Python), Byte-Sized-Chunks: Decision Trees and Random Forests, An Introduction to Deep Learning & Computer Vision, Byte-Sized-Chunks: Recommendation Systems, and From 0 to 1: Learn Python Programming – Easy as Pie.

Lam Wing Kee, 61, a Hong Kong bookseller who was imprisoned in China has told the BBC he considered taking his own life while in custody. Mr Lam was one of five booksellers targeted by officials for selling material critical of the Chinese leadership. Speaking to the BBC's Juliana Liu, he said: "You can stand up against tyranny."

One of five Hong Kong booksellers who went missing in mysterious circumstances last year has said he had been detained for more than eight months by Chinese authorities. Lam Wing-kee announced on Thursday that he was arrested in the southern Chinese city of Shenzhen and that his colleague, Lee Bo, who went missing from Hong Kong in December, had also been abducted. Following months of speculation about the circumstances surrounding the disappearances, Lam called a surprise press conference just two days after being released. Lam said he was taken on a 14-hour train journey to the eastern city of Ningbo following his arrest. There, he was kept in a small room by himself, and repeatedly interrogated about the selling of banned books on the mainland.

R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly. The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

We present an initial proposal for modular object-oriented MDPs, an extension of OO-MDPs that abstracts complex domains that are partially observable and stochastic with multiple goals. Modes reduce the curse of dimensionality by reducing the number of attributes, objects, and actions into only the features relevant for each goal. These modes may also be used as an abstracted domain to be transferred to other modes or to another domain.

Viewpoint estimation, especially in case of multiple object classes, remains an important and challenging problem. First, objects under different views undergo extreme appearance variations, often making within-class variance larger than between-class variance. Second, obtaining precise ground truth for real-world images, necessary for training supervised viewpoint estimation models, is extremely difficult and time consuming. As a result, annotated data is often available only for a limited number of classes. Hence it is desirable to share viewpoint information across classes. Additional complexity arises from unaligned pose labels between classes, i.e. a side view of a car might look more like a frontal view of a toaster, than its side view. To address these problems, we propose a metric learning approach for joint class prediction and pose estimation. Our approach allows to circumvent the problem of viewpoint alignment across multiple classes, and does not require dense viewpoint labels. Moreover, we show, that the learned metric generalizes to new classes, for which the pose labels are not available, and therefore makes it possible to use only partially annotated training sets, relying on the intrinsic similarities in the viewpoint manifolds. We evaluate our approach on two challenging multi-class datasets, 3DObjects and PASCAL3D+.

Years ago, when I made a switch from procedural to object oriented programming, concepts such as function overloading fascinated me. The simplicity a single function changing and behaving based on the types of values passed to it spoke volumes to its simplicity and elegance. Being a bit nostalgic I am going to say "those were the good old days!". Today, the word Analytics is certainly an overloaded term in the data world! It is used to define work done by data scientists to business analysts and from execution of sophisticated statistical algorithms to the use of simple visualization tools.