Temporal Reasoning: A Three Way Analysis. - Vineet Padmanabhan; Abdul Sattar 001; Arun K. Pujari; Chinmoy Goswami (TIME, 2000)

Actions Made Explicit in BDI. - Vineet Padmanabhan; Guido Governatori; Abdul Sattar 001 (Australian Joint Conference on Artificial Intelligence, 2001)

A Defeasible Logic of Policy-Based Intention. - Guido Governatori; Vineet Padmanabhan; Abdul Sattar 001 (Australian Joint Conference on Artificial Intelligence, 2002)

On Fibring Semantics for BDI Logics. - Guido Governatori; Vineet Padmanabhan; Abdul Sattar 001 (JELIA, 2002)

A Defeasible Logic of Policy-Based Intention. - Guido Governatori; Vineet Padmanabhan (Australian Conference on Artificial Intelligence, 2003)

Information Distortion in a Supply Chain: The Bullwhip Effect. - Hau L. Lee; Vineet Padmanabhan; Seungjin Whang (Manag. Sci., 2004)

Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect". - Hau L. Lee; Vineet Padmanabhan; Seungjin Whang (Manag. Sci., 2004)

Observation-based Model for BDI-Agents. - Kaile Su; Abdul Sattar 001; Kewen Wang 001; Xiangyu Luo; Guido Governatori; Vineet Padmanabhan (AAAI, 2005)

Using a temporal constraint network for business process execution. - Ruopeng Lu; Shazia Sadiq; Vineet Padmanabhan; Guido Governatori (ADC, 2006)

Process modelling: the deontic way. - Vineet Padmanabhan; Guido Governatori; Shazia Sadiq; Robert M. Colomb; Antonino Rotolo (APCCM, 2006)

The cost of social agents. - Guido Governatori; Antonino Rotolo; Vineet Padmanabhan (AAMAS, 2006)

A Fibred Tableau Calculus for Modal Logics of Agents. - Vineet Padmanabhan; Guido Governatori (DALT, 2006)

Rule-Based Agents in Temporalised Defeasible Logic. - Guido Governatori; Vineet Padmanabhan; Antonino Rotolo (PRICAI, 2006)

On Constructing Fibred Tableaux for BDI Logics. - Vineet Padmanabhan; Guido Governatori (PRICAI, 2006)

Dialogue Games in Defeasible Logic. - Subhasis Thakur; Guido Governatori; Vineet Padmanabhan; Jenny Eriksson Lundström (Australian Conference on Artificial Intelligence, 2007)

An Asymmetric Protocol for Argumentation Games in Defeasible Logic. - Jenny Eriksson Lundström; Guido Governatori; Subhasis Thakur; Vineet Padmanabhan (PRIMA, 2007)

Knowledge Assessment: A Modal Logic Approach. - Vineet Padmanabhan; Guido Governatori; Subhasis Thakur (PRIMA, 2008)

Research Note - A Cross-Category Model of Households' Incidence and Quantity Decisions. - Rakesh Niraj; Vineet Padmanabhan; P. B. Seetharaman (Mark. Sci., 2008)

A defeasible logic for modelling policy-based intentions and motivational attitudes. - Guido Governatori; Vineet Padmanabhan; Antonino Rotolo; Abdul Sattar 001 (Log. J. IGPL, 2009)

Incorporating Temporal Planning Within a BDI Architecture. - Vineet Padmanabhan; Abdul Sattar 001; Guido Governatori; Kollapalli Ramesh Babu (IICAI, 2011)

Reasoning about DNSSEC. - Kollapalli Ramesh Babu; Vineet Padmanabhan; Wilson Naik Bhukya (MIWAI, 2011)

Fibred BDI Logics: Completeness Preservation in the Presence of Interaction Axioms. - Vineet Padmanabhan; Guido Governatori; Abdul Sattar 001 (MIWAI, 2011)

A Rule Based Approach to Group Recommender Systems. - Vineet Padmanabhan; Siva Krishna Seemala; Wilson Naik Bhukya (MIWAI, 2011)

Crisis and Consumption Smoothing. - Pushan Dutt; Vineet Padmanabhan (Mark. Sci., 2011)

Content Contributor Management and Network Effects in a UGC Environment. - Kaifu Zhang; Theodoros Evgeniou; Vineet Padmanabhan; Emile Richard (Mark. Sci., 2012)

Group Recommender Systems: A Virtual User Approach Based on Precedence Mining. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan (Australasian Conference on Artificial Intelligence, 2013)

Time Series Qlet: Invariant approach for data mining. - Abhishek Anand; Vineet Padmanabhan (IC3, 2013)

Training and classification of ballistic missiles using Hidden Markov model. - Upendra Kumar Singh; Vineet Padmanabhan (IC3, 2013)

Group Recommender Systems - Some Experimental Results. - Vineet Padmanabhan; Prabhu Kiran; Abdul Sattar 001 (ICAART (2), 2013)

A novel method for training and classification of ballistic and quasi-ballistic missiles in real-time. - Upendra Kumar Singh; Vineet Padmanabhan; Arun Agarwal (IJCNN, 2013)

Precedence Mining in Group Recommender Systems. - Venkateswara Rao Kagita; Vineet Padmanabhan; Arun K. Pujari (PReMI, 2013)

Training by ART-2 and Classification of Ballistic Missiles Using Hidden Markov Model. - Upendra Kumar Singh; Vineet Padmanabhan (PReMI, 2013)

An Approach to Content Based Recommender Systems Using Decision List Based Classification with k-DNF Rule Set. - Abinash Pujahari; Vineet Padmanabhan (ICIT, 2014)

Collaborative filtering by PSO-based MMMF. - Sowmini Devi V.; Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan (SMC, 2014)

Dynamic classification of ballistic missiles using neural networks and hidden Markov models. - Upendra Kumar Singh; Vineet Padmanabhan; Arun Agarwal (Appl. Soft Comput., 2014)

Algebraic Modeling and Verification of Web Service Composition. - Gopal N. Rai; G. R. Gangadharan; Vineet Padmanabhan (ANT/SEIT, 2015)

Bi-directional Search for Skyline Probability. - Arun K. Pujari; Venkateswara Rao Kagita; Anubhuti Garg; Vineet Padmanabhan (CALDAM, 2015)

A Novel Social-Choice Strategy for Group Modeling in Recommender Systems. - Venkateswara Rao Kagita; Krishna Charan Meka; Vineet Padmanabhan (ICIT, 2015)

Topic Modelling for Songs. - Nishma Laitonjam; Vineet Padmanabhan; Arun K. Pujari; Rajendra Prasad Lal (ICIT, 2015)

Learning in Real-Time Strategy Games. - Vineet Padmanabhan; Pranay Goud; Arun K. Pujari; Harshit Sethy (ICIT, 2015)

Group Recommender Systems: Combining User-User and Item-Item Collaborative Filtering Techniques. - Abinash Pujahari; Vineet Padmanabhan (ICIT, 2015)

GP-SVM: Tree Structured Multiclass SVM with Greedy Partitioning. - Sandeep Kumar Sahu; Arun K. Pujari; Venkateswara Rao Kagita; Vikas Kumar 003; Vineet Padmanabhan (ICIT, 2015)

Recommender system algorithms: A comparative analysis based on monotonicity. - Tadiparthi V. R. Himabindu; Vineet Padmanabhan; Venkateswara Rao Kagita; Arun K. Pujari (ICAPR, 2015)

Greedy partitioning based tree structured multiclass SVM for Odia OCR. - Sandeep Kumar Sahu; Arun K. Pujari; Vikas Kumar 003; Venkateswara Rao Kagita; Vineet Padmanabhan (NCVPRIPG, 2015)

Virtual user approach for group recommender systems using precedence relations. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan (Inf. Sci., 2015)

Efficient computation for probabilistic skyline over uncertain preferences. - Arun K. Pujari; Venkateswara Rao Kagita; Anubhuti Garg; Vineet Padmanabhan (Inf. Sci., 2015)

Collaborative Filtering, Matrix Factorization and Population Based Search: The Nexus Unveiled. - Ayangleima Laishram; Satya Prakash Sahu; Vineet Padmanabhan; Siba Kumar Udgata (ICONIP (3), 2016)

Prediction with Confidence in Item Based Collaborative Filtering. - Tadiparthi V. R. Himabindu; Vineet Padmanabhan; Arun K. Pujari; Abdul Sattar 001 (PRICAI, 2016)

Threshold-Based Direct Computation of Skyline Objects for Database with Uncertain Preferences. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003; Sandeep Kumar Sahu (PRICAI, 2016)

A Matrix Factorization & Clustering Based Approach for Transfer Learning. - Sowmini Devi V.; Vineet Padmanabhan; Arun K. Pujari (PReMI, 2017)

Divide and Transfer: Understanding Latent Factors for Recommendation Tasks. - Vidyadhar Rao; Rosni K. Vasu; Vineet Padmanabhan (RecSysKTL, 2017)

Bounds on skyline probability for databases with uncertain preferences. - Arun K. Pujari; Vineet Padmanabhan; Venkateswara Rao Kagita (Int. J. Approx. Reason., 2017)

Conformal recommender system. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Sandeep Kumar Sahu; Vikas Kumar 003 (Inf. Sci., 2017)

Collaborative filtering using multiple binary maximum margin matrix factorizations. - Vikas Kumar 003; Arun K. Pujari; Sandeep Kumar Sahu; Venkateswara Rao Kagita; Vineet Padmanabhan (Inf. Sci., 2017)

Proximal maximum margin matrix factorization for collaborative filtering. - Vikas Kumar 003; Arun K. Pujari; Sandeep Kumar Sahu; Venkateswara Rao Kagita; Vineet Padmanabhan (Pattern Recognit. Lett., 2017)

BDI Based Performance Enhancement in DNSSEC. - Kollapalli Ramesh Babu; Vineet Padmanabhan (ICDCIT, 2018)

Multi-cell LSTM Based Neural Language Model. - Thomas Cherian; Akshay Badola; Vineet Padmanabhan (CoRR, 2018)

Multi-label classification using hierarchical embedding. - Vikas Kumar 003; Arun K. Pujari; Vineet Padmanabhan; Sandeep Kumar Sahu; Venkateswara Rao Kagita (Expert Syst. Appl., 2018)

Conformal matrix factorization based recommender system. - Tadiparthi V. R. Himabindu; Vineet Padmanabhan; Arun K. Pujari (Inf. Sci., 2018)

Enhanced Collaborative Filtering Through User-Item Subgroups, Particle Swarm Optimization and Fuzzy C-Means. - Ayangleima Laishram; Vineet Padmanabhan (Canadian AI, 2019)

BMF: Matrix Factorization of Large Scale Data Using Block Based Approach. - Prasad Bhavana; Vineet Padmanabhan (PRICAI (2), 2019)

Discovery of user-item subgroups via genetic algorithm for effective prediction of ratings in collaborative filtering. - Ayangleima Laishram; Vineet Padmanabhan (Appl. Intell., 2019)

A Maximum Margin Matrix Factorization based Transfer Learning Approach for Cross-Domain Recommendation. - Sowmini Devi Veeramachaneni; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (Appl. Soft Comput., 2019)

Committee Selection with Attribute Level Preferences. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (CoRR, 2019)

Block based Singular Value Decomposition approach to matrix factorization for recommender systems. - Prasad Bhavana; Vikas Kumar 003; Vineet Padmanabhan (CoRR, 2019)

Group preserving label embedding for multi-label classification. - Vikas Kumar 003; Arun K. Pujari; Vineet Padmanabhan; Venkateswara Rao Kagita (Pattern Recognit., 2019)

Skyline recommendation with uncertain preferences. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (Pattern Recognit. Lett., 2019)

Committee Selection using Attribute Approvals. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Haris Aziz 001; Vikas Kumar 003 (AAMAS, 2021)

Matrix factorization of large scale data using multistage matrix factorization. - Prasad Bhavana; Vineet Padmanabhan (Appl. Intell., 2021)

A Hinge-Loss based Codebook Transfer for Cross-Domain Recommendation with Nonoverlapping Data. - Sowmini Devi Veeramachaneni; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (CoRR, 2021)

Identifying Class Specific Filters with L1 Norm Frequency Histograms in Deep CNNs. - Akshay Badola; Cherian Roy; Vineet Padmanabhan; Rajendra Prasad Lal (CoRR, 2021)

Web Service Interaction Modeling and Verification Using Recursive Composition Algebra. - Gopal N. Rai; G. R. Gangadharan; Vineet Padmanabhan; Rajkumar Buyya (IEEE Trans. Serv. Comput., 2021)

Systematic Monotonicity and Consistency for Adversarial Natural Language Inference. - Brahmani Nutakki; Akshay Badola; Vineet Padmanabhan (AI, 2022)

Transfer of codebook latent factors for cross-domain recommendation with non-overlapping data. - Sowmini Devi Veeramachaneni; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (CoRR, 2022)

A hinge-loss based codebook transfer for cross-domain recommendation with non-overlapping data. - Sowmini Devi Veeramachaneni; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (Inf. Syst., 2022)

Inductive conformal recommender system. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (Knowl. Based Syst., 2022)

Re-examining Class Selectivity in Deep Convolutional Networks. - Akshay Badola; Vineet Padmanabhan; Rajendra Prasad Lal (MIWAI, 2023)

Content Based Network Representational Learning for Movie Recommendation (CNMovieRec). - Nageswar Rao Kota; Vineet Padmanabhan; Wilson Naik Bhukya (MIWAI, 2023)

GPU accelerated matrix factorization of large scale data using block based approach. - Prasad Bhavana; Vineet Padmanabhan (CoRR, 2023)

Decomposing the deep: finding class-specific filters in deep CNNs. - Akshay Badola; Cherian Roy; Vineet Padmanabhan; Rajendra Prasad Lal (Neural Comput. Appl., 2023)

Matrix Factorization of Large Scale Data Using Block Based Approach and GPU Acceleration. - Prasad Bhavana; Vineet Padmanabhan; Wilson Naik Bhukya (BDA, 2024)

Efficient Self-Supervised Contrastive Learning with Representation Mixing. - Yash Kumar Sharma; Akshay Badola; Vineet Padmanabhan; Wilson Naik; Abdul Sattar 001 (BDA, 2024)

Interpretable Visual Semantic Alignment via Spectral Attribution. - Shivanvitha Ambati; Vineet Padmanabhan; Wilson Naik Bhukya; Rajendra Prasad Lal (ICPR (26), 2024)

Temporal Matrix Factorization: A polynomial approach to latent factor estimation. - Prasad Bhavana; Vineet Padmanabhan (Pattern Recognit., 2025)