• Publications
  • Influence
Perfect Matchings in 3-Uniform Hypergraphs with Large Vertex Degree
  • Imdadullah Khan
  • Computer Science, Mathematics
  • SIAM J. Discret. Math.
  • 30 January 2011
TLDR
A perfect matching in a 3-uniform hypergraph on $n=3k$ vertices is a subset of $\frac{n}{3}$ disjoint edges. Expand
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Scalable Approximation Algorithm for Graph Summarization
TLDR
We propose a novel weighted sampling scheme to sample vertices for merging that will result in the least reconstruction error. Expand
  • 8
  • 2
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Perfect matchings in 4-uniform hypergraphs
  • Imdadullah Khan
  • Computer Science, Mathematics
  • J. Comb. Theory, Ser. B
  • 28 January 2011
A perfect matching in a 4-uniform hypergraph on n vertices is a subset of ? n 4 ? disjoint edges. We prove that if H is a sufficiently large 4-uniform hypergraph on n = 4 k vertices such that everyExpand
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Efficient Approximation Algorithms for Strings Kernel Based Sequence Classification
TLDR
Sequence classification algorithms, such as SVM, require a definition of distance (similarity) measure between two sequences. Expand
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  • 1
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Short Term Load Forecasting using Smart Meter Data
TLDR
Accurate short term electricity load forecasting is crucial for efficient operations of the power sector. Expand
  • 6
Generalized Similarity Kernels for Efficient Sequence Classification
TLDR
We propose a novel computational framework that uses general similarity metrics and distance-preserving embeddings with string kernels to improve sequence classification. Expand
  • 3
A Multi-cascaded Model with Data Augmentation for Enhanced Paraphrase Detection in Short Texts
TLDR
We present a data augmentation strategy and a multi-cascaded model for improved paraphrase detection in short texts. Expand
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A Multi-cascaded Deep Model for Bilingual SMS Classification
TLDR
We propose a novel multi-cascaded deep learning model called McM for bilingual SMS classification. Expand
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Estimating Descriptors for Large Graphs
TLDR
In this work, we propose streaming algorithms to efficiently approximate descriptors by estimating counts of sub-graphs of order \documentclass[12pt]{minimal} \usepackage{amsmath} through Budgeted Estimates, and thereby devise extensions of two existing graph comparison paradigms. Expand
  • 2
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Generalized Similarity Kernels for Efficient Sequence Classification
TLDR
We propose a novel computational framework that uses general similarity metrics S(·, ·) and distance-preserving embeddings with string kernels to improve sequence classification. Expand
  • 7
  • PDF
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