Controlled dual perturbations for l p -programming. - Shu-Cherng Fang; Jay Rajasekera (Z. Oper. Research, 1986)

Controlled perturbations for quadratically constrained quadratic programs. - Shu-Cherng Fang; J. R. Rajasekera (Math. Program., 1986)

A perturbation approach to the main duality theorem of quadratic geometric programming. - Shu-Cherng Fang; Jay Rajasekera (Z. Oper. Research, 1987)

Quadratically constrained minimum cross-entropy analysis. - Shu-Cherng Fang; J. R. Rajasekera (Math. Program., 1989)

On the convex programming approach to linear programming. - J. R. Rajasekera; Shu-Cherng Fang (Oper. Res. Lett., 1991)

Entropy Optimization Models with Convex Constraints - Shu-Cherng Fang; J. R. Rajasekera (Inf. Comput., 1995)

Estimating the Firm Value Distribution Function by Entropy Optimization and Geometric Programming. - J. R. Rajasekera; M. Yamada (Ann. Oper. Res., 2001)

An Important Issue in Data Mining : Data Cleaning. - Qi Xiao Yang; Sam Yuan Sung; Chun Lu; Jay Rajasekera (PACLIC, 2002)

Using Kansei Engineering with new JIT to accomplish cost advantage. - Jay Rajasekera; Shantanu Dayal (Int. J. Biom., 2010)

An Emotion and Attention Recognition System to Classify the Level of Engagement to a Video Conversation by Participants in Real Time Using Machine Learning Models and Utilizing a Neural Accelerator Chip. - Janith Kodithuwakku; Dilki Dandeniya Arachchi; Jay Rajasekera (Algorithms, 2022)

Efficient Online Engagement Analytics Algorithm Toolkit That Can Run on Edge. - Saw Thiha; Jay Rajasekera (Algorithms, 2023)