16,109 research outputs found
On Frankl and Furedi's conjecture for 3-uniform hypergraphs
The Lagrangian of a hypergraph has been a useful tool in hypergraph extremal
problems. In most applications, we need an upper bound for the Lagrangian of a
hypergraph. Frankl and Furedi in \cite{FF} conjectured that the -graph with
edges formed by taking the first sets in the colex ordering of
has the largest Lagrangian of all -graphs with
edges. In this paper, we give some partial results for this conjecture.Comment: 19 pages, 1 figure. arXiv admin note: substantial text overlap with
arXiv:1211.650
Discriminative Segmental Cascades for Feature-Rich Phone Recognition
Discriminative segmental models, such as segmental conditional random fields
(SCRFs) and segmental structured support vector machines (SSVMs), have had
success in speech recognition via both lattice rescoring and first-pass
decoding. However, such models suffer from slow decoding, hampering the use of
computationally expensive features, such as segment neural networks or other
high-order features. A typical solution is to use approximate decoding, either
by beam pruning in a single pass or by beam pruning to generate a lattice
followed by a second pass. In this work, we study discriminative segmental
models trained with a hinge loss (i.e., segmental structured SVMs). We show
that beam search is not suitable for learning rescoring models in this
approach, though it gives good approximate decoding performance when the model
is already well-trained. Instead, we consider an approach inspired by
structured prediction cascades, which use max-marginal pruning to generate
lattices. We obtain a high-accuracy phonetic recognition system with several
expensive feature types: a segment neural network, a second-order language
model, and second-order phone boundary features
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