Sciweavers

NIPS
2004
13 years 11 months ago
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
We consider the situation in semi-supervised learning, where the "label sampling" mechanism stochastically depends on the true response (as well as potentially on the fe...
Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie
NIPS
2004
13 years 11 months ago
Semi-Markov Conditional Random Fields for Information Extraction
We describe semi-Markov conditional random fields (semi-CRFs), a conditionally trained version of semi-Markov chains. Intuitively, a semiCRF on an input sequence x outputs a "...
Sunita Sarawagi, William W. Cohen
NIPS
2004
13 years 11 months ago
Following Curved Regularized Optimization Solution Paths
Regularization plays a central role in the analysis of modern data, where non-regularized fitting is likely to lead to over-fitted models, useless for both prediction and interpre...
Saharon Rosset
NIPS
2004
13 years 11 months ago
Learning, Regularization and Ill-Posed Inverse Problems
Many works have shown that strong connections relate learning from examples to regularization techniques for ill-posed inverse problems. Nevertheless by now there was no formal ev...
Lorenzo Rosasco, Andrea Caponnetto, Ernesto De Vit...
NIPS
2004
13 years 11 months ago
Semi-parametric Exponential Family PCA
We present a semi-parametric latent variable model based technique for density modelling, dimensionality reduction and visualization. Unlike previous methods, we estimate the late...
Sajama, Alon Orlitsky
NIPS
2004
13 years 11 months ago
Coarticulation in Markov Decision Processes
We investigate an approach for simultaneously committing to multiple activities, each modeled as a temporally extended action in a semi-Markov decision process (SMDP). For each ac...
Khashayar Rohanimanesh, Robert Platt Jr., Sridhar ...
NIPS
2004
13 years 11 months ago
Using Random Forests in the Structured Language Model
In this paper, we explore the use of Random Forests (RFs) in the structured language model (SLM), which uses rich syntactic information in predicting the next word based on words ...
Peng Xu, Frederick Jelinek
NIPS
2004
13 years 11 months ago
Brain Inspired Reinforcement Learning
Successful application of reinforcement learning algorithms often involves considerable hand-crafting of the necessary non-linear features to reduce the complexity of the value fu...
François Rivest, Yoshua Bengio, John Kalask...
NIPS
2004
13 years 11 months ago
An Information Maximization Model of Eye Movements
We propose a sequential information maximization model as a general strategy for programming eye movements. The model reconstructs high-resolution visual information from a sequen...
Laura Walker Renninger, James M. Coughlan, Preeti ...
NIPS
2004
13 years 11 months ago
Chemosensory Processing in a Spiking Model of the Olfactory Bulb: Chemotopic Convergence and Center Surround Inhibition
This paper presents a neuromorphic model of two olfactory signalprocessing primitives: chemotopic convergence of olfactory receptor neurons, and center on-off surround lateral inh...
Baranidharan Raman, Ricardo Gutierrez-Osuna