Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents;researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.

/pdf/intelligent-agents-theory-and-practice-5dchj7p8pc.pdf

Intelligent Agents: Theory and Practice

物件導向軟體之架構(Object-Oriented Software Construction)探討

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Lock Coarsening

We present a generalization of standard typestate systems in which the typestate of each object is determined by its membership in a collection of abstract typestate sets. This generalization supports typestates that model participation in abstract data types, composite typestates that correspond to membership in multiple sets, and hierarchical typestates. Because membership in typestate sets corresponds directly to participation in data structures, our typestate system characterizes global sharing patterns.In our approach, each module encapsulates a data structure and uses membership in abstract sets to characterize how objects participate in its data structure. Each analysis verifies that the implementation of the module 1) preserves important internal data structure representation invariants and 2) conforms to a specification that uses formulas in a set algebra to characterize the effects of operations on the data structure. The analyses use the common set abstraction to 1) characterize how objects participate in multiple data structures and to 2) enable the inter-analysis communication required to verify properties that depend on multiple modules analyzed by different analyses.

http://lara.epfl.ch/~kuncak/papers/LamETAL04GeneralizedTypestateCheckingUsingSets.pdf

Generalized typestate checking using set interfaces and pluggable analyses

We present a set of techniques for reducing the memory consumption of object-oriented programs. These techniques include analysis algorithms and optimizations that use the results of these analyses to eliminate fields with constant values, reduce the sizes of fields based on the range of values that can appear in each field, and eliminate fields with common default values or usage patterns. We apply these optimizations both to fields declared by the programmer and to implicit fields in the runtime object header. Although it is possible to apply these techniques to any object-oriented program, we expect they will be particularly appropriate for memory-limited embedded systems.We have implemented these techniques in the MIT FLEX compiler system and applied them to the programs in the SPECjvm98 benchmark suite. Our experimental results show that our combined techniques can reduce the maximum live heap size required for the programs in our benchmark suite by as much as 40%. Some of the optimizations reduce the overall execution time; others may impose modest performance penalties.

/pdf/data-size-optimizations-for-java-programs-50np7040r7.pdf

Data size optimizations for java programs

We present Prioni, a tool that integrates model checking and theorem proving for relational reasoning. Prioni takes as input formulas written in Alloy, a declarative language based on relations. Prioni uses the Alloy Analyzer to check the validity of Alloy formulas for a given scope that bounds the universe of discourse. The Alloy Analyzer can refute a formula if a counterexample exists within the given scope, but cannot prove that the formula holds for all scopes. For proofs, Prioni uses Athena, a denotational proof language. Prioni translates Alloy formulas into Athena proof obligations and uses the Athena tool for proof discovery and checking.

/pdf/integrating-model-checking-and-theorem-proving-for-4c2pw74mc7.pdf

Integrating Model Checking and Theorem Proving for Relational Reasoning

We introduce inference metaprogramming for probabilistic programming languages, including new language constructs, a formalism, and the rst demonstration of e ectiveness in practice. Instead of relying on rigid black-box inference algorithms hard-coded into the language implementation as in previous probabilistic programming languages, infer- ence metaprogramming enables developers to 1) dynamically decompose inference problems into subproblems, 2) apply in- ference tactics to subproblems, 3) alternate between incorpo- rating new data and performing inference over existing data, and 4) explore multiple execution traces of the probabilis- tic program at once. Implemented tactics include gradient- based optimization, Markov chain Monte Carlo, variational inference, and sequental Monte Carlo techniques. Inference metaprogramming enables the concise expression of proba- bilistic models and inference algorithms across diverse elds, such as computer vision, data science, and robotics, within a single probabilistic programming language.

Martin Rinard

Papers

Lock Coarsening

Generalized typestate checking using set interfaces and pluggable analyses

Data size optimizations for java programs

Integrating Model Checking and Theorem Proving for Relational Reasoning

Probabilistic programming with programmable inference