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- Alexander H. Waibel, Toshiyuki Hanazawa, Geoffrey E. Hinton, Kiyohiro Shikano, Kevin J. Lang
- IEEE Trans. Acoustics, Speech, and Signal…
- 1989

In this paper we present a Time-Delay Neural Network (TDNN) approach to phoneme recognition which is characterized by two important properties. 1) Using a 3 layer arrangement of simple computing units, a hierarchy can be constructed that allows for the formation of arbitrary nonlinear decision surfaces. The TDNN learns these decision surfaces automatically… (More)

- Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Michael W. Mahoney
- Internet Mathematics
- 2009

A large body of work has been devoted to defining and identifying clusters or communities in social and information networks, i.e., in graphs in which the nodes represent underlying social entities and the edges represent some sort of interaction between pairs of nodes. Most such research begins with the premise that a community or a cluster should be… (More)

- Reid Andersen, Fan Chung Graham, Kevin J. Lang
- 2006 47th Annual IEEE Symposium on Foundations of…
- 2006

A local graph partitioning algorithm finds a cut near a specified starting vertex, with a running time that depends largely on the size of the small side of the cut, rather than the size of the input graph. In this paper, we present a local partitioning algorithm using a variation of PageRank with a specified starting distribution. We derive a mixing result… (More)

A large body of work has been devoted to identifying community structure in networks. A community is often though of as a set of nodes that has more connections between its members than to the remainder of the network. In this paper, we characterize as a function of size the statistical and structural properties of such sets of nodes. We define the network… (More)

- Kevin J. Lang, Barak A. Pearlmutter, Rodney A. Price
- ICGI
- 1998

This paper first describes the structure and results of the Abbadingo One DFA Learning Competition. The competition was designed to encourage work on algorithms that scale well—both to larger DFAs and to sparser training data. We then describe and discuss the winning algorithm of Rodney Price, which orders state merges according to the amount of evidence in… (More)

- Jure Leskovec, Kevin J. Lang, Michael W. Mahoney
- WWW
- 2010

Detecting clusters or communities in large real-world graphs such as large social or information networks is a problem of considerable interest. In practice, one typically chooses an objective function that captures the intuition of a network cluster as set of nodes with better internal connectivity than external connectivity, and then one applies… (More)

- Kevin J. Lang, Alexander H. Waibel, Geoffrey E. Hinton
- Neural Networks
- 1990

A translation-invariant back-propagation network is described that performs better than a soph&ticated continuous acoustic parameter hidden Markov model on a noisy, lO0-speaker confusable vocabulary isolated word recognition task. The network's replicated architecture permits it to extract precise information from unaligned training patterns selected by a… (More)

- Jonathan M. D. Hill, William F. McColl, +6 authors Rob H. Bisseling
- Parallel Computing
- 1998

BSPlib is a small communications library for bulk synchronous parallel (BSP) programming which consists of only 20 basic operations. This paper presents the full deenition of BSPlib in C, motivates the design of its basic operations, and gives examples of their use. The library enables programming in two distinct styles: direct remote memory access using… (More)

- Reid Andersen, Kevin J. Lang
- SODA
- 2008

We present an algorithm called Improve that improves a proposed partition of a graph, taking as input a subset of vertices and returning a new subset of vertices with a smaller quotient cut score. The most powerful previously known method for improving quotient cuts, which is based on parametric flow, returns a partition whose quotient cut score is at least… (More)

- Reid Andersen, Kevin J. Lang
- WWW
- 2006

Expanding a seed set into a larger community is a common procedure in link-based analysis. We show how to adapt recent results from theoretical computer science to expand a seed set into a community with small conductance and a strong relationship to the seed, while examining only a small neighborhood of the entire graph. We extend existing results to give… (More)