AT&T Labs

About: AT&T Labs is a based out in . It is known for research contribution in the topics: Network packet & The Internet. The organization has 1879 authors who have published 5595 publications receiving 483151 citations.

Marking text documents

Abstract: Summary form only given. Electronic documents are more easily copied and redistributed than paper documents. This is a major impediment to electronic publishing. Illegal redistribution can be discouraged by placing unique marks in each copy and registering the copy with the original recipient. If an illegal copy is discovered, the original recipient can be identified. We describe several invisible techniques for encoding information in text documents. We also describe a marking system, for electronic publishing, that is scalable to large numbers of users.

How to avoid unwanted email

Abstract: U nwanted communication ranges from nuisance (junk mail) to annoyance (telemarketing) to dangerous to the very medium conveying the message (junk fax, obscene or harassing telephone calls). The usefulness of email is seriously threatened by the commercialization of the Internet because it is easier than ever to collect address lists and cheaper than ever to mass-distribute messages. If companies spent as much money sending junk email as they do sending junk physical mail, an established Internet user would likely get more than 100 junk messages per day. Every time a user sends a message to a public newsgroup or list, fills out a Web form, or mails in a product registration card, the server cheaply obtains an email address and usually some indication of the user's interests. This information is then sold to marketing firms that easily automate mass emailings of advertisements , surveys, and other annoyances that cost the user connect time and, worse, valuable attention. More sinister unwanted email is becoming common as well, including harassing and hate mail. The main technique today for avoiding unwanted communication is to restrict the set of people to whom users give their addresses. For example, people pay to avoid having their phone numbers listed; in email, people sometimes maintain multiple email accounts, using different accounts for different purposes , such as commercial vs. personal. This unlisted address approach is expensive and slow to recover from security breaches; if an address is leaked to an adversary, the only alternative is to pay the service provider to change it (often a lengthy process). Once Despite looking like conventional email, a channelized email address and its related agent allow email users to reliably cut off unwanted correspondents.

Spatial Superchannel Routing in a Two-Span ROADM System for Space Division Multiplexing

Abstract: We report a two-span, 67-km space-division-multiplexed (SDM) wavelength-division-multiplexed (WDM) system incorporating the first reconfigurable optical add-drop multiplexer (ROADM) supporting spatial superchannels and the first cladding-pumped multicore erbium-doped fiber amplifier directly spliced to multicore transmission fiber. The ROADM subsystem utilizes two conventional 1 × 20 wavelength selective switches (WSS) each configured to implement a 7 × (1 × 2) WSS. ROADM performance tests indicate that the subchannel insertion losses, attenuation accuracies, and passband widths are well matched to each other and show no significant penalty, compared to the conventional operating mode for the WSS. For 6 × 40 × 128-Gb/s SDM-WDM polarization-multiplexed quadrature phase-shift-keyed (PM-QPSK) transmission on 50 GHz spacing, optical signal-to-noise ratio penalties are less than 1.6 dB in Add, Drop, and Express paths. In addition, we demonstrate the feasibility of utilizing joint signal processing of subchannels in this two-span, ROADM system.

Comparing the effectiveness of several modeling methods for fault prediction

Abstract: We compare the effectiveness of four modeling methods--negative binomial regression, recursive partitioning, random forests and Bayesian additive regression trees--for predicting the files likely to contain the most faults for 28 to 35 releases of three large industrial software systems. Predictor variables included lines of code, file age, faults in the previous release, changes in the previous two releases, and programming language. To compare the effectiveness of the different models, we use two metrics--the percent of faults contained in the top 20% of files identified by the model, and a new, more general metric, the fault-percentile-average. The negative binomial regression and random forests models performed significantly better than recursive partitioning and Bayesian additive regression trees, as assessed by either of the metrics. For each of the three systems, the negative binomial and random forests models identified 20% of the files in each release that contained an average of 76% to 94% of the faults.

Approximate nearest neighbors and sequence comparison with block operations

Abstract: We study sequence nearest neighbors (SNN). Let D be a database of n sequences; we would like to preprocess D so that given any on-line query sequence Q we can quickly find a sequence S in D for which d(S;Q) d(S; T ) for any other sequence T in D. Hered(S;Q) denotes the distance between sequences S andQ, defined to be the minimum number of edit operations needed to transform one to another (all edit operations will be reversible so thatd(S; T ) = d(T; S) for any two sequencesT andS). These operations correspond to the notion of similarity between sequences that we wish to capture in a given application. Natural edit operations include character edits (inserts, replacements, deletes etc), block edits (moves, copies, deletes, reversals) and block numerical transformations (scaling by an additive or a multiplicative constant). The SNN problem arises in many applications. We present the first known efficient algorithm for “approximate” nearest neighbor search for sequences with preprocessing time and space polynomial in size of D and query time near-linear in size of Q. We assume the distanced(S; T ) between two sequences S andT is the minimum number of character edits and block operations needed to transform one to the other. The approximation factor we achieve is O(log `(log `)2), where` is the size of the longest sequence in D. In addition, AT& T Labs – Research, 180 Park Avenue, Florham Park, NJ 07932; email: muthu@research.att.com. yDepartment of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106 ; email:cenk@eecs.cwru.edu. we also give an algorithm for exactly computing the distance between two sequences when edit operations of the type character replacements and block reversals are allowed. The time and space requirements of the algorithm is near linear; previously known approaches take at least quadratic time.