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ECCV
2006
Springer
16 years 1 months ago
Riemannian Manifold Learning for Nonlinear Dimensionality Reduction
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
Tony Lin, Hongbin Zha, Sang Uk Lee
ICPR
2004
IEEE
16 years 29 days ago
Type-2 Fuzzy Hidden Markov Models to Phoneme Recognition
This paper presents a novel extension of Hidden Markov Models (HMMs): type-2 fuzzy HMMs (type-2 FHMMs). The advantage of this extension is that it can handle both randomness and f...
Jia Zeng, Zhi-Qiang Liu
STOC
2004
ACM
142views Algorithms» more  STOC 2004»
16 years 5 days ago
Lower bounds for local search by quantum arguments
The problem of finding a local minimum of a black-box function is central for understanding local search as well as quantum adiabatic algorithms. For functions on the Boolean hype...
Scott Aaronson
DATE
2009
IEEE
125views Hardware» more  DATE 2009»
15 years 6 months ago
Finite precision processing in wireless applications
—Complex signal processing algorithms are often specified in floating point precision. Thus, a type conversion is needed when the targeted platform requires fixed-point precis...
David Novo, Min Li, Bruno Bougard, Liesbet Van der...
IROS
2009
IEEE
163views Robotics» more  IROS 2009»
15 years 6 months ago
On the performance of random linear projections for sampling-based motion planning
— Sampling-based motion planners are often used to solve very high-dimensional planning problems. Many recent algorithms use projections of the state space to estimate properties...
Ioan Alexandru Sucan, Lydia E. Kavraki