Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

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

In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers.



Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others.



The material is organized according to the system model-first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference.



The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms-to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures.


Table of Contents

1 Introduction 
2 Modelling I; Synchronous Network Model 
3 Leader Election in a Synchronous Ring 
4 Algorithms in General Synchronous Networks 
5 Distributed Consensus with Link Failures 
6 Distributed Consensus with Process Failures 
7 More Consensus Problems 
8 Modelling II: Asynchronous System Model 
9 Modelling III: Asynchronous Shared Memory Model 
10 Mutual Exclusion 
11 Resource Allocation 
12 Consensus 
13 Atomic Objects 
14 Modelling IV: Asynchronous Network Model 
15 Basic Asynchronous Network Algorithms 
16 Synchronizers 
17 Shared Memory versus Networks 
18 Logical Time 
19 Global Snapshots and Stable Properties 
20 Network Resource Allocation 
21 Asynchronous Networks with Process Failures 
22 Data Link Protocols 
23 Partially Synchronous System Models 
24 Mutual Exclusion with Partial Synchrony 
25 Consensus with Partial Synchrony

Distributed algorithms

We review the field of cavity optomechanics, which explores the interaction between electromagnetic radiation and nano- or micromechanical motion This review covers the basics of optical cavities and mechanical resonators, their mutual optomechanical interaction mediated by the radiation pressure force, the large variety of experimental systems which exhibit this interaction, optical measurements of mechanical motion, dynamical backaction amplification and cooling, nonlinear dynamics, multimode optomechanics, and proposals for future cavity quantum optomechanics experiments In addition, we describe the perspectives for fundamental quantum physics and for possible applications of optomechanical devices

Cavity Optomechanics

This paper studies information-theoretically secure quantum homomorphic encryption (QHE) schemes of classical data. Previous works on information-theoretically secure QHE schemes (like Childs'05, Liang'13, and others) are typically based on the Quantum-One-Time-Pad (QOTP) approach of Ambainis et al. [AMTdW'00]. There, the encryption of a bit is a qubit, randomly selected from a set of four possible qubits. This paper takes a different approach and presents the RBE (Random-Basis Encryption) scheme -- a QHE scheme in which the encryption of a bit is a qubit, randomly selected from a set of an immense number of qubits. Second, this paper studies weak measurements (WM) and presents a WM-based attack on legacy QOTP-based Quantum Key Distribution (QKD) protocols. Then, we use the RBE scheme to construct a QKD protocol and argue that this protocol is resilient to such WM-based attacks. Finally, this paper raises the following question. Entanglement is an essential resource in quantum information and quantum computation research. Hence, once generated, how can its owner secure entangled systems of qubits? We inspect possible QOTP-based solutions, suggest an RBE-based solution, and discuss some of the benefits of the latter.

Randomly Choose an Angle from an Immense Number of Angles to Rotate Qubits, Compute and Reverse

This work describes probabilistic methods for utilizing random spanning trees generated via a random walk process. Goyal et al. showed that the union of random spanning trees approximates the expansion of every cut of a graph. First, we generalize the method by Goyal et al. for weighted graphs and show that it is possible to approximate the expansion of every cut in a weighted graph with the union of random spanning trees generated by a random walk on a weighted graph. Second, we show that our union of random spanning trees is a spectral sparsifier of the graph. Moreover, we show that $O(\log n /\epsilon^2)$ random spanning trees are required in order to spectrally approximate a bounded degree graph. This result closes a previously open question on the number of random spanning trees required for saprsification. Third, we show that our random spanning trees based construction provides security features for virtual networks, in the context of Software-Defined Networking. Network virtualization coupled with Software-Defined Networking allows new on-demand management capabilities. We demonstrate such a service, namely, on-demand efficient monitoring or anonymity. The proposed service is based on network virtualization of expanders or sparsifiers over the physical network. The defined virtual (or overlay) communication graphs coupled with a multi-hop extension of Valiant randomization based routing lets us monitor the entire traffic in the network, with a very few monitoring nodes. We propose methods that theoretically improve services provided by existing monitoring or anonymity networks, and optimize the degree of monitoring or anonymity.

Random Spanning Trees for Expanders, Sparsifiers, and Virtual Network Security

W e present a historical overview of how computer science (CS) was introduced in schools in Israel. We analyze the importance of the inclusion of CS in school curricula, for the individual development of pupils’ capabilities in all facets, and for Israel’s society and economy. We stress the need to expose all pupils to CS in a seamless learning gamified approach, in a spiral deepening of the two essential complementing aspects of CS—algorithms and programming. We start with perceptible physical moving robots that demonstrate an unbiased reaction of algorithms and programs, and gradually train for developing capabilities to abstract data structures, algorithms, and programs. We detail the journey of the introduction of computer science to the Israel Education system. The CS Curricula are described starting with elementary school, into middle school and then high school. Implementation issues are also briefly discussed. Finally, we discuss our vision for future developments in Israel’s CS education.

The journey of computer science and software engineering in Israeli schools

This paper demonstrates and proves that the coordination of actions in a distributed swarm can be enhanced by using quantum entanglement. In particular, we focus on• Global and local simultaneous random walks, using entangled qubits that collapse into the same (or opposite) direction, either random direction or totally controlled simultaneous movements.• Identifying eavesdropping from malicious eavesdroppers aimed at disturbing the simultaneous random walks by using entangled qubits that were sent at random or with predefined bases.

Distributed Coordination Based on Quantum Entanglement (Work in Progress)

The invention is a service provided to a user by the operators of a communication network. The service of the invention comprises an application process that is associated with a specific user. The application process permanently represents the user, and accompanies the user wherever he/she is located. The application process of the invention acts on behalf of a user of the network performing the functions of monitoring, processing (e.g. encryption/decryption services), performing backup, and data transmission.

Shlomi Dolev

Papers

Randomly Choose an Angle from an Immense Number of Angles to Rotate Qubits, Compute and Reverse

Random Spanning Trees for Expanders, Sparsifiers, and Virtual Network Security

The journey of computer science and software engineering in Israeli schools

Distributed Coordination Based on Quantum Entanglement (Work in Progress)

Avatar process for mobile devices