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www.isi.edu/~riesa
A hierarchical syntax-based word alignment package for statistical machine translation Nile is a supervised, discriminative word alignment package that uses nonlocal, overlapping features. For details, see: "Feature-Rich Language-Independent Syntax-Based Alignment for Statistical Machine Translation" (J. Riesa, A. Irvine, and D. Marcu), Proceedings of EMNLP 2011. "Hierarchical Search for Word Alig
www.isi.edu/~yuri
Dupx is a simple *nix utility to redirect standard output/input/error of an already running process. Motivation I've often found myself in a situation where a process I started on a remote system via SSH takes much longer than I had anticipated. I need to break the SSH connection, but if I do so, the process will die if it tries to write something on stdout/error of a broken pipe. I wish I could s
www.isi.edu
The Network Simulator: Building Ns This page describes ns version 2. Where to Start What hardware is needed? To build ns you need a computer and a C++ compiler. We develop ns on several kinds of Unix (FreeBSD, Linux, SunOS, Solaris), so it installs smoothest there, but it should run on an Posix-like computer, possibly with some tweaking. Ns also builds and runs under Windows, see the dedicated Win
www.isi.edu/~sravi
Using Structured Text for Large-Scale Attribute Extraction Sujith Ravi ∗ University of Southern California Information Sciences Institute Marina del Rey, California 90292 sravi@isi.edu Marius Pa¸sca Google Inc. 1600 Amphitheatre Parkway Mountain View, California 94043 mars@google.com ABSTRACT We propose a weakly-supervised approach for extracting class attributes from structured text available wi
What's Nam Nam is a Tcl/TK based animation tool for viewing network simulation traces and real world packet traces. It supports topology layout, packet level animation, and various data inspection tools. Nam began at LBL. It has evolved substantially over the past few years. The nam development effort was an ongoing collaboration with the VINT project. Currently, it is being developed as an open s
Kristina Lerman is a Senior Principal Scientist at the Information Sciences Institute and holds a joint appointment as a Research Professor in the USC Viterbi School of Engineering's Computer Science Department. Her research focuses on applying network- and machine learning-based methods to problems in social computing. Lerman’s research aims to harness the power of AI in a connected world. Her pa
www.isi.edu/~knight
Welcome Projects We conduct research in adaptive, self-reconfigurable, autonomous robots and systems, including StarCell, modular, multifunctional and self-reconfigurable SuperBot, Hormone-Inspired Control (HIC), Surprise-Based Learning (SBL), self-healing MORPHOS robots, self-reconfiguration Distributed Planner, self-reconfigurable, optimizing and healing networks LANdroids, self-assembly SOLAR r
www.isi.edu/~hdaume
The VINT Project A collaboration between researchers at UC Berkeley, LBL, USC/ISI, and Xerox PARC. Kevin Fall, Editor Kannan Varadhan, Editor http://www-nrg.ee.lbl.gov/ns/ ©../copyright.html is LBNL's Network Simulator [24]. The simulator is written in C++; it uses OTcl as a command and configuration interface. v2 has three substantial changes from v1: (1) the more complex objects in v1 have been
The Natural Language Group at the USC Information Sciences Institute conducts research in natural language processing and computational linguistics, developing new linguistic and mathematical techniques to make better technology. We have a wide range of ongoing projects, including those related to statistical machine translation, question answering, summarization, ontologies, information retrieval
Note: The project has migrated these web pages to a wiki. This page can now be found here. Ns is a discrete event simulator targeted at networking research. Ns provides substantial support for simulation of TCP, routing, and multicast protocols over wired and wireless (local and satellite) networks. Ns began as a variant of the REAL network simulator in 1989 and has evolved substantially over the
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