Since artificial neural networks allow modeling of nonlinear processes, they have turned into a very popular and useful tool for solving many problems such as classification, clustering, regression…
2020-2021 International Conferences in Artificial Intelligence, Machine Learning, Computer Vision, Data Mining, Natural Language Processing and Robotics
We introduce a new lambda calculus with futures, Lambda(fut), that models the operational semantics of concurrent statically typed functional programming languages with mixed eager and lazy threads such as Alice ML, a concurrent extension of Standard ML. Lambda(fut) is a minimalist extension of the call-by-value lambda-calculus that is sufficiently expressive to define and combine a variety of standard concurrency abstractions, such as channels, semaphores, and ports. Despite its minimality, the basic machinery of Lambda(fut) is sufficiently powerful to support explicit recursion and call-by-need evaluation. We present a static type system for Lambda(fut) and distinguish a fragment of Lambda(fut) that we prove to be uniformly confluent. This result confirms our intuition that reference cells are the sole source of indeterminism.
Mahout currently has
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Dirichlet process clustering
Latent Dirichlet Allocation
Singular value decomposition
Parallel Frequent Pattern mining
Complementary Naive Bayes classifier
Random forest decision tree based classifier
High performance java collections (previously colt collections)
A vibrant community
and many more cool stuff to come by this summer thanks to Google summer of code
I'm interested in machine learning techniques (graphical models, kernel methods) applied to text understanding (entity and relation extraction, coreference resolution, document classification and clustering, confidence prediction, social network analysis, data mining).
Some Basics on ATS ATS consists of a static component (statics), where types are formed and reasoned about, and a dynamic component (dynamics), where programs are constructed and evaluated. Some Primitive Sorts and Constants The statics of ATS is a simply typed language. The types for terms in the statics are called sorts (so as to avoid potential confusion with the types for terms in the dynamics) and the terms in it are called static terms. We use sigma for sorts and s for static term. The primitive sorts in ATS include bool, int, prop, type, view and viewtype. There are also some primitive constants c in the statics, each of which is assigned a constant sort (or c-sort, for short) of the following form:
Bayesian Methods for Hackers : An intro to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view.
In order to better understand complex Belief-Propagation models tested with our simulator we have identified a strong need for a simple visualization tool that will grant us insight of the tested graphs.
M. Thimm, и G. Kern-Isberner. Proceedings of the 2nd International Conference on Computational Models of Argument (COMMA'08), стр. 381--392. IOS Press, (мая 2008)
T. Sato, и Y.Kameya. Working Notes of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL-04), стр. 94--101. Banff, Alberta, Canada, (июля 2004)
M. Minsky. The Psychology of Computer Vision, McGraw-Hill, New York, Alternative version is in reason:Haugeland97a, and reprinted in reason:BraLev85b.(1975)