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NIPS
1997
15 years 5 months ago
Nonlinear Markov Networks for Continuous Variables
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
Reimar Hofmann, Volker Tresp
MSOM
2007
118views more  MSOM 2007»
15 years 3 months ago
What Can Be Learned from Classical Inventory Models? A Cross-Industry Exploratory Investigation
: Classical inventory models offer a variety of insights into the optimal way to manage inventories of individual products. However, top managers and industry analysts are often co...
Sergey Rumyantsev, Serguei Netessine
ICDM
2010
IEEE
273views Data Mining» more  ICDM 2010»
15 years 2 months ago
Learning Maximum Lag for Grouped Graphical Granger Models
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
Amit Dhurandhar
ALT
1997
Springer
15 years 8 months ago
Learning DFA from Simple Examples
Efficient learning of DFA is a challenging research problem in grammatical inference. It is known that both exact and approximate (in the PAC sense) identifiability of DFA is har...
Rajesh Parekh, Vasant Honavar
ICALT
2007
IEEE
15 years 10 months ago
The application of IMS Learning Design to Develop Compute-based Educational Game
How can game designers realize the balance of “educational function” and “entertainment” in a Computer-based Educational Game (CEG)? The concept of IMS learning design (LD...
Miaomiao Zeng, Yueliang Zhou