J. Bala

REFERENCES (2009)

D. Ackley, G. Hinton, T. Sejnowski, E. Farguell, F. Mazzanti, E. Gómez-ramírez, ...

HOD process. Therefore, there is a tradeoff between memory and computing time. HOD provides a direct solution for the learning algorithm. In comparison, tuning the MC algorithm to provide lower error...

The MONK's Problems APerformance Comparison of Di erent Learning Algorithms (2008)

S. B. Thrun, J. Bala, E. Bloedorn, I. Bratko, B. Cestnik, J. Cheng, ...

Once upon a time, in July 1991, the monks of Corsendonk Priory were faced with a school held in their priory, namely the 2 nd European Summer School on Machine Learning. After listening more than one...

Initial Results (2007)

R. S. Michalski, J. W. Bala, P. W. Pachowicz, R. Michalski, J. Bala, P. Pachowicz

Spin wave excitations in ferromagnetic manganites with orbital order (2005)

Bala, J., Oleś, A. M.

Spin-orbital physics in the optical conductivity of quarter-filled manganites (2005)

Bala, J., Horsch, P.

Origin of band and localized electron states in photoemission of NiO (2000)

Bala, J., Oles, A.M., Zaanen, J.

Origin of band and localized electron states in photoemission of NiO (2000)

Bala, J., Oles, A.M., Zaanen, J.

Quasiparticles in the spin-fermion model for CuO2 planes (1996)

Bala, J., Oles, A.M., Zaanen, J.

Quasiparticles in the spin-fermion model for CuO2 planes (1996)

Bala, J., Oles, A.M., Zaanen, J.

Using Learning to Facilitate the Evolution of Features for Recognizing Visual Concepts (1996)

Bala Datamat Systems, J. Bala, K. De Jong, J. Huang, H. Vafaie, H. Wechsler

: This paper describes a hybrid methodology that integrates genetic algorithms and decision tree learning in order to evolve useful subsets of discriminatory features for recognizing complex visual...

Visual Routine for Eye Detection Using Hybrid Genetic Architectures (1996)

Bala Dejong Huang, J. Bala, K. Dejong, J. Huang, H. Vafaie, H. Wechsler

We address the problem of crafting visual routines for detection tasks. Emphasis is placed on both competition and learning to help with specific visual tasks involved in localization and...

Using Learning to Facilitate the Evolution of Features for Recognizing Visual Concepts (1996)

J. Bala, K. De Jong, J. Huang, H. Vafaie, H. Wechsler

: This paper describes a hybrid methodology that integrates genetic algorithms and decision tree learning in order to evolve useful subsets of discriminatory features for recognizing complex visual...

Visual Routine for Eye Detection Using Hybrid Genetic Architectures (1996)

J. Bala, K. Dejong, J. Huang, H. Vafaie, H. Wechsler

We address the problem of crafting visual routines for detection tasks. Emphasis is placed on both competition and learning to help with specific visual tasks involved in localization and...

Spin polarons in the t-t'-j model (1995)

Bala, J., Oles, A.M., Zaanen, J.

Spin polarons in the t-t'-j model (1995)

Bala, J., Oles, A.M., Zaanen, J.

Spin polarons in the t-t'-j model (1995)

Bala, J., Oles, A.M., Zaanen, J.

Spin polarons in the t-t'-j model (1995)

Bala, J., Oles, A.M., Zaanen, J.

Hybrid Learning Using Genetic Algorithms and Decision Trees for Pattern Classification (1995)

Bala Huang And, J. Bala, J. Huang, H. Vafaie

This paper introduces a hybrid learning methodology that integrates genetic algorithms (GAs) and decision tree learning (ID3) in order to evolve optimal subsets of discriminatory features for robust...

Hybrid Learning Using Genetic Algorithms and Decision Trees for Pattern Classification (1995)

J. Bala, J. Huang, H. Vafaie, K. Dejong, H. Wechsler

This paper introduces a hybrid learning methodology that integrates genetic algorithms (GAs) and decision tree learning (ID3) in order to evolve optimal subsets of discriminatory features for robust...

Hybrid learning using genetic algorithms and decision trees for pattern classification (1995)

J. Bala, J. Huang, H. Vafaie

This paper introduces a hybrid learning methodology that integrates genetic algorithms (GAs) and decision tree learning (ID3) in order to evolve optimal subsets of discriminatory features for robust...

Zhang-rice localization and quasi-particles in cuo2 planes (1994)

Bala, J., Oles, A.M., Zaanen, J.

Zhang-rice localization, quasi-particle dispersions, and the photoemission of nio (1994)

Bala, J., Oles, A.M., Zaanen, J.

Zhang-rice localization and quasi-particles in cuo2 planes (1994)

Bala, J., Oles, A.M., Zaanen, J.

Zhang-rice localization, quasi-particle dispersions, and the photoemission of nio (1994)

Bala, J., Oles, A.M., Zaanen, J.

The principal axes method for constructive induction (1992)

J. Bala, R. S. Michalski, J. Wnek, Jerzy W. Bala, Ryszard S. Michalski, Janusz Wnek

The paper describes a novel method for consreactive induction, called PRAX (Principal Axes). The madeflying idea of the method is to determine descriptions of a class of certain basic concepts, and...

Recognition of Textural Concepts Through Multilevel Symbolic Transformations (1991)

J. Bala, R. S. Michalski, Ryszard S. Michalski

This paper presents the TEXTRAL system, used for determining structural visual properties of textures through symbolic transformations. The 'method consists of two phases: one that extracts...

The MONK's Problems A Performance Comparison of Different Learning Algorithms (1991)

S. B. Thrun, J. Bala, E. Bloedorn, I. Bratko, B. Cestnik, J. Cheng, ...

This report summarizes a comparison of different learning techniques which was performed at the 2nd European Summer School on Machine Learning, held in Belgium during summer 1991. A variety of...