A fast procedure for computing the distance between complex objects in three space. - Elmer G. Gilbert; Daniel W. Johnson; S. Sathiya Keerthi (ICRA, 1987)

A fast procedure for computing the distance between complex objects in three-dimensional space. - Elmer G. Gilbert; Daniel W. Johnson; S. Sathiya Keerthi (IEEE J. Robotics Autom., 1988)

A new approach to the numerical solution of constrained mechanical system dynamics. - S. Sathiya Keerthi; Rachuri Sudarsan; N. K. Sancheti (ICRA, 1992)

Computation of certain measures of proximity between convex polytopes: a complexity viewpoint. - N. K. Sancheti; S. Sathiya Keerthi (ICRA, 1992)

Path planning: an approach based on connecting all the minimizers and maximizers of a potential function. - H. Shashikala; N. K. Sancheti; S. Sathiya Keerthi (ICRA, 1992)

A homotopy approach for stabilizing single-input systems with control structure constraints. - Makarand S. Phatak; S. Sathiya Keerthi (Autom., 1992)

Translational Motion Planning for a Convex Polyhedron in a 3D Polyhedral World Using an Efficient and New Roadmap. - Abhi Dattasharma; S. Sathiya Keerthi (CCCG, 1993)

Optimal Control of a Somersaulting Platform Diver: A Numerical Approach. - Nukala V. R. K. N. Murthy; S. Sathiya Keerthi (ICRA (1), 1993)

Numerical Determination of Optimal Non-Holonomic Paths in the Presence of Obstacles. - Sudhaker Samuel; S. Sathiya Keerthi (ICRA (1), 1993)

On Computing a Distance Measure for Path Planning. - K. Sridharan 001; Harry E. Stephanou; S. Sathiya Keerthi (ICRA (1), 1993)

Distance Measures on Intersecting Objects and Their Applications. - K. Sridharan 001; Harry E. Stephanou; K. C. Craig; S. Sathiya Keerthi (Inf. Process. Lett., 1994)

Algorithms for the Optimal Loading of Recursive Neural Nets. - Vijay Chandru; Abhi Dattasharma; S. Sathiya Keerthi; N. K. Sancheti; V. Vinay (SODA, 1995)

Regional pole placement of multivariable systems under control structure constraints. - S. Sathiya Keerthi; Makarand S. Phatak (IEEE Trans. Autom. Control., 1995)

An Augmented Voronoi Roadmap for 3D Translational Motion Planning for a Convex Polyhedron Moving Amidst Convex Polyhedral Obstacles. - Abhi Dattasharma; S. Sathiya Keerthi (Theor. Comput. Sci., 1995)

Numerical approaches for solution of differential equations on manifolds. - Rachuri Sudarsan; S. Sathiya Keerthi (Appl. Math. Comput., 1998)

An efficient approach for the numerical simulation of multibody systems. - Rachuri Sudarsan; S. Sathiya Keerthi (Appl. Math. Comput., 1998)

Synthesis of fault-tolerant feedforward neural networks using minimax optimization. - Dipti Deodhare; M. Vidyasagar; S. Sathiya Keerthi (IEEE Trans. Neural Networks, 1998)

Context Filters for Document-based Information Filtering. - K. R. K. Murthy; S. Sathiya Keerthi (ICDAR, 1999)

A Study of Representations for Pen based Handwriting Recognition of Tamil Characters. - C. S. Sundaresan; S. Sathiya Keerthi (ICDAR, 1999)

EquiDistance Diagram: A New Roadmap Method for Path Planning. - S. Sathiya Keerthi; Chong Jin Ong; Eugene Huang; Elmer G. Gilbert (ICRA, 1999)

Predictive App roaches for Choosing Hyperparameters in Gaussian Processes. - S. Sundararajan; S. Sathiya Keerthi (NIPS, 1999)

A Variational Mean-Field Theory for Sigmoidal Belief Networks. - Chiranjib Bhattacharyya; S. Sathiya Keerthi (NIPS, 2000)

A fast iterative nearest point algorithm for support vector machine classifier design. - S. Sathiya Keerthi; Shirish K. Shevade; Chiranjib Bhattacharyya; K. R. K. Murthy (IEEE Trans. Neural Networks Learn. Syst., 2000)

Improvements to the SMO algorithm for SVM regression. - Shirish K. Shevade; S. Sathiya Keerthi; Chiranjib Bhattacharyya; K. R. K. Murthy (IEEE Trans. Neural Networks Learn. Syst., 2000)

A stochastic connectionist approach for global optimization with application to pattern clustering. - G. Phanendra Babu; M. Narasimha Murty; S. Sathiya Keerthi (IEEE Trans. Syst. Man Cybern. Part B, 2000)

A Unified Loss Function in Bayesian Framework for Support Vector Regression. - Wei Chu; S. Sathiya Keerthi; Chong Jin Ong (ICML, 2001)

Mean Field Methods for a Special Class of Belief Networks. - Chiranjib Bhattacharyya; S. Sathiya Keerthi (J. Artif. Intell. Res., 2001)

Computation of a penetration measure between 3D convex polyhedral objects for collision detection. - K. Sridharan 001; S. Sathiya Keerthi (J. Field Robotics, 2001)

Improvements to Platt's SMO Algorithm for SVM Classifier Design. - S. Sathiya Keerthi; Shirish K. Shevade; Chiranjib Bhattacharyya; K. R. K. Murthy (Neural Comput., 2001)

Predictive Approaches for Choosing Hyperparameters in Gaussian Processes. - S. Sundararajan; S. Sathiya Keerthi (Neural Comput., 2001)

Rule prepending and post-pruning approach to incremental learning of decision lists. - K. R. K. Murthy; S. Sathiya Keerthi; M. Narasimha Murty (Pattern Recognit., 2001)

Reference governor control of constrained feedback systems using neural networks. - Harshad Jahagirdar; S. Sathiya Keerthi; Marcelo H. Ang Jr. (ISIC, 2002)

Convergence of a Generalized SMO Algorithm for SVM Classifier Design. - S. Sathiya Keerthi; Elmer G. Gilbert (Mach. Learn., 2002)

A Machine Learning Approach for the Curation of Biomedical Literature - KDD Cup 2002 (Task 1). - S. Sathiya Keerthi; Chong Jin Ong; Keng Boon Siah; David B. L. Lim; Wei Chu; Min Shi; David S. Edwin; Rakesh Menon; Lixiang Shen; Jonathan Y. K. Lim; Han Tong Loh (SIGKDD Explor., 2002)

Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms. - S. Sathiya Keerthi (IEEE Trans. Neural Networks, 2002)

A Machine Learning Approach for the Curation of Biomedical Literature. - Min Shi; David S. Edwin; Rakesh Menon; Lixiang Shen; Jonathan Y. K. Lim; Han Tong Loh; S. Sathiya Keerthi; Chong Jin Ong (ECIR, 2003)

SMO algorithm for least squares SVM. - S. Sathiya Keerthi; Shirish K. Shevade (IJCNN, 2003)

Automated Text Classification for Fast Feedback - Investigating the Effects of Document Representation. - Rakesh Menon; Han Tong Loh; S. Sathiya Keerthi; Aarnout Brombacher (KES, 2003)

Multi-category Classification by Soft-Max Combination of Binary Classifiers. - Kaibo Duan; S. Sathiya Keerthi; Wei Chu; Shirish Krishnaj Shevade; Aun Neow Poo (Multiple Classifier Systems, 2003)

A simple and efficient algorithm for gene selection using sparse logistic regression. - Shirish K. Shevade; S. Sathiya Keerthi (Bioinform., 2003)

Special issue on support vector machines. - Colin Campbell; Chih-Jen Lin; S. Sathiya Keerthi; V. David Sánchez A. (Neurocomputing, 2003)

Evaluation of simple performance measures for tuning SVM hyperparameters. - Kaibo Duan; S. Sathiya Keerthi; Aun Neow Poo (Neurocomputing, 2003)

Bayesian Trigonometric Support Vector Classifier. - Wei Chu; S. Sathiya Keerthi; Chong Jin Ong (Neural Comput., 2003)

Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel. - S. Sathiya Keerthi; Chih-Jen Lin (Neural Comput., 2003)

SMO Algorithm for Least-Squares SVM Formulation. - S. Sathiya Keerthi; Shirish K. Shevade (Neural Comput., 2003)

Predictive Approaches for Sparse Model Learning. - Shirish K. Shevade; S. Sundararajan; S. Sathiya Keerthi (ICONIP, 2004)

Stability regions for constrained nonlinear systems and their functional characterization via support-vector-machine learning. - Chong Jin Ong; S. Sathiya Keerthi; Elmer G. Gilbert; Z. H. Zhang (Autom., 2004)

Bayesian support vector regression using a unified loss function. - Wei Chu; S. Sathiya Keerthi; Chong Jin Ong (IEEE Trans. Neural Networks, 2004)

An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels. - Martin M. S. Lee; S. Sathiya Keerthi; Chong Jin Ong; Dennis DeCoste (IEEE Trans. Neural Networks, 2004)

New approaches to support vector ordinal regression. - Wei Chu; S. Sathiya Keerthi (ICML, 2005)

Generalized LARS as an effective feature selection tool for text classification with SVMs. - S. Sathiya Keerthi (ICML, 2005)

Which Is the Best Multiclass SVM Method? An Empirical Study. - Kaibo Duan; S. Sathiya Keerthi (Multiple Classifier Systems, 2005)

A matching pursuit approach to sparse Gaussian process regression. - S. Sathiya Keerthi; Wei Chu (NIPS, 2005)

A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs. - S. Sathiya Keerthi; Dennis DeCoste (J. Mach. Learn. Res., 2005)

A Fast Dual Algorithm for Kernel Logistic Regression. - S. Sathiya Keerthi; Kaibo Duan; Shirish K. Shevade; Aun Neow Poo (Mach. Learn., 2005)

Analyzing textual databases using data mining to enable fast product development processes. - Rakesh Menon; Han Tong Loh; S. Sathiya Keerthi (Reliab. Eng. Syst. Saf., 2005)

An improved conjugate gradient scheme to the solution of least squares SVM. - Wei Chu; Chong Jin Ong; S. Sathiya Keerthi (IEEE Trans. Neural Networks, 2005)

Bayesian Support Vector Machines for Feature Ranking and Selection. - Wei Chu; S. Sathiya Keerthi; Chong Jin Ong; Zoubin Ghahramani (Feature Extraction, 2006)

Deterministic annealing for semi-supervised kernel machines. - Vikas Sindhwani; S. Sathiya Keerthi; Olivier Chapelle (ICML, 2006)

Branch and Bound for Semi-Supervised Support Vector Machines. - Olivier Chapelle; Vikas Sindhwani; S. Sathiya Keerthi (NIPS, 2006)

Relational Learning with Gaussian Processes. - Wei Chu; Vikas Sindhwani; Zoubin Ghahramani; S. Sathiya Keerthi (NIPS, 2006)

An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models. - S. Sathiya Keerthi; Vikas Sindhwani; Olivier Chapelle (NIPS, 2006)

Large scale semi-supervised linear SVMs. - Vikas Sindhwani; S. Sathiya Keerthi (SIGIR, 2006)

Developing parallel sequential minimal optimization for fast training support vector machine. - Lijuan Cao; S. Sathiya Keerthi; Chong Jin Ong; P. Uvaraj; Xiuju Fu; H. P. Lee (Neurocomputing, 2006)

Building Support Vector Machines with Reduced Classifier Complexity. - S. Sathiya Keerthi; Olivier Chapelle; Dennis DeCoste (J. Mach. Learn. Res., 2006)

Parallel sequential minimal optimization for the training of support vector machines. - Lijuan Cao; S. Sathiya Keerthi; Chong Jin Ong; J. Q. Zhang; U. Periyathamby; Xiuju Fu; H. P. Lee (IEEE Trans. Neural Networks, 2006)

Trust region Newton methods for large-scale logistic regression. - Chih-Jen Lin; Ruby C. Weng; S. Sathiya Keerthi (ICML, 2007)

Semi-Supervised Gaussian Process Classifiers. - Vikas Sindhwani; Wei Chu; S. Sathiya Keerthi (IJCAI, 2007)

Constructing a maximum utility slate of on-line advertisements - S. Sathiya Keerthi; John A. Tomlin (CoRR, 2007)

Support Vector Ordinal Regression. - Wei Chu; S. Sathiya Keerthi (Neural Comput., 2007)

Fast Generalized Cross-Validation Algorithm for Sparse Model Learning. - S. Sundararajan; Shirish K. Shevade; S. Sathiya Keerthi (Neural Comput., 2007)

A Fast Tracking Algorithm for Generalized LARS/LASSO. - S. Sathiya Keerthi; Shirish K. Shevade (IEEE Trans. Neural Networks, 2007)

A dual coordinate descent method for large-scale linear SVM. - Cho-Jui Hsieh; Kai-Wei Chang; Chih-Jen Lin; S. Sathiya Keerthi; S. Sundararajan (ICML, 2008)

A sequential dual method for large scale multi-class linear svms. - S. Sathiya Keerthi; S. Sundararajan; Kai-Wei Chang; Cho-Jui Hsieh; Chih-Jen Lin (KDD, 2008)

Optimization Techniques for Semi-Supervised Support Vector Machines. - Olivier Chapelle; Vikas Sindhwani; S. Sathiya Keerthi (J. Mach. Learn. Res., 2008)

Trust Region Newton Method for Logistic Regression. - Chih-Jen Lin; Ruby C. Weng; S. Sathiya Keerthi (J. Mach. Learn. Res., 2008)

A web of concepts. - Nilesh N. Dalvi; Ravi Kumar 001; Bo Pang 001; Raghu Ramakrishnan 001; Andrew Tomkins; Philip Bohannon; S. Sathiya Keerthi; Srujana Merugu (PODS, 2009)

Efficient algorithms for ranking with SVMs. - Olivier Chapelle; S. Sathiya Keerthi (Inf. Retr., 2010)

Semi-supervised multi-task learning of structured prediction models for web information extraction. - Paramveer S. Dhillon; Sundararajan Sellamanickam; Sathiya Keerthi Selvaraj (CIKM, 2011)

A pairwise ranking based approach to learning with positive and unlabeled examples. - Sundararajan Sellamanickam; Priyanka Garg; Sathiya Keerthi Selvaraj (CIKM, 2011)

Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset. - Sathiya Keerthi Selvaraj; Bigyan Bhar; Sundararajan Sellamanickam; Shirish K. Shevade (CIKM, 2011)

A Sequential Dual Method for Structural SVMs. - Shirish K. Shevade; P. Balamurugan 001; S. Sundararajan; S. Sathiya Keerthi (SDM, 2011)

Iterative Viterbi A* Algorithm for K-Best Sequential Decoding. - Zhiheng Huang; Yi Chang 001; Bo Long; Jean-François Crespo; Anlei Dong; S. Sathiya Keerthi; Su-Lin Wu (ACL (1), 2012)

Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses. - Sathiya Keerthi Selvaraj; Sundararajan Sellamanickam; Shirish K. Shevade (COLING (Posters), 2012)

Regularized Structured Output Learning with Partial Labels. - Sundararajan Sellamanickam; Charu Tiwari; Sathiya Keerthi Selvaraj (SDM, 2012)

Automatic web-scale information extraction. - Philip Bohannon; Nilesh N. Dalvi; Yuval Filmus; Nori Jacoby; S. Sathiya Keerthi; Alok Kirpal (SIGMOD Conference, 2012)

Graph Based Classification Methods Using Inaccurate External Classifier Information - Sundararajan Sellamanickam; Sathiya Keerthi Selvaraj (CoRR, 2012)

Transductive Classification Methods for Mixed Graphs - Sundararajan Sellamanickam; Sathiya Keerthi Selvaraj (CoRR, 2012)

Predictive Approaches For Gaussian Process Classifier Model Selection - Sundararajan Sellamanickam; Sathiya Keerthi Selvaraj (CoRR, 2012)

Deterministic Annealing for Semi-Supervised Structured Output Learning. - Paramveer S. Dhillon; S. Sathiya Keerthi; Kedar Bellare; Olivier Chapelle; Sundararajan Sellamanickam (AISTATS, 2012)

Tractable Semi-supervised Learning of Complex Structured Prediction Models. - Kai-Wei Chang; S. Sundararajan; S. Sathiya Keerthi (ECML/PKDD (3), 2013)

A Structured Prediction Approach for Missing Value Imputation. - Rahul Kidambi; Vinod Nair; Sundararajan Sellamanickam; S. Sathiya Keerthi (CoRR, 2013)

A Functional Approximation Based Distributed Learning Algorithm. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan; Léon Bottou (CoRR, 2013)

A Parallel SGD method with Strong Convergence. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan; Léon Bottou (CoRR, 2013)

A Quantitative Evaluation Framework for Missing Value Imputation Algorithms. - Vinod Nair; Rahul Kidambi; Sundararajan Sellamanickam; S. Sathiya Keerthi; Johannes Gehrke; Vijay Narayanan (CoRR, 2013)

An Empirical Evaluation of Sequence-Tagging Trainers. - P. Balamurugan 001; Shirish K. Shevade; S. Sundararajan; S. Sathiya Keerthi (CoRR, 2013)

A Distributed Algorithm for Training Nonlinear Kernel Machines. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan (CoRR, 2014)

A distributed block coordinate descent method for training $l_1$ regularized linear classifiers. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan (CoRR, 2014)

Near Real-Time Service Monitoring Using High-Dimensional Time Series. - Shwetabh Khanduja; Vinod Nair; S. Sundararajan; Ameya Raul; Ajesh Babu Shaj; S. Sathiya Keerthi (ICDM Workshops, 2015)

Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues. - Vinod Nair; Ameya Raul; Shwetabh Khanduja; Vikas Bahirwani; Sundararajan Sellamanickam; S. Sathiya Keerthi; Steve Herbert; Sudheer Dhulipalla (KDD, 2015)

Towards a Better Understanding of Predict and Count Models. - S. Sathiya Keerthi; Tobias Schnabel; Rajiv Khanna (CoRR, 2015)

Hashtag Recommendation for Enterprise Applications. - Dhruv Mahajan 001; Vishwajit Kolathur; Chetan Bansal; Suresh Parthasarathy; Sundararajan Sellamanickam; S. Sathiya Keerthi; Johannes Gehrke (CIKM, 2016)

Learning Semantically Coherent and Reusable Kernels in Convolution Neural Nets for Sentence Classification. - Madhusudan Lakshmana; Sundararajan Sellamanickam; Shirish K. Shevade; Sathiya Keerthi Selvaraj (CoRR, 2016)

Gradient Boosted Decision Trees for High Dimensional Sparse Output. - Si Si; Huan Zhang 001; S. Sathiya Keerthi; Dhruv Mahajan 001; Inderjit S. Dhillon; Cho-Jui Hsieh (ICML, 2017)

Batch-Expansion Training: An Efficient Optimization Paradigm for Machine Learning. - Michal Derezinski; Dhruv Mahajan 001; S. Sathiya Keerthi; S. V. N. Vishwanathan; Markus Weimer (CoRR, 2017)

Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles. - Dhruv Mahajan 001; Vivek Gupta 001; S. Sathiya Keerthi; Sundararajan Sellamanickam; Shravan Narayanamurthy; Rahul Kidambi (CoRR, 2017)

A distributed block coordinate descent method for training l1 regularized linear classifiers. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan (J. Mach. Learn. Res., 2017)

Batch-Expansion Training: An Efficient Optimization Framework. - Michal Derezinski; Dhruv Mahajan 001; S. Sathiya Keerthi; S. V. N. Vishwanathan; Markus Weimer (AISTATS, 2018)

Learning State Representations for Query Optimization with Deep Reinforcement Learning. - Jennifer Ortiz; Magdalena Balazinska; Johannes Gehrke; S. Sathiya Keerthi (DEEM@SIGMOD, 2018)

An efficient distributed learning algorithm based on effective local functional approximations. - Dhruv Mahajan 001; Nikunj Agrawal; S. Sathiya Keerthi; Sundararajan Sellamanickam; Léon Bottou (J. Mach. Learn. Res., 2018)

Distributed Newton Methods for Deep Neural Networks. - Chien-Chih Wang; Kent Loong Tan; Chun-Ting Chen; Yu-Hsiang Lin; S. Sathiya Keerthi; Dhruv Mahajan 001; S. Sundararajan; Chih-Jen Lin (Neural Comput., 2018)

Targeted display advertising: the case of preferential attachment. - Saurav Manchanda; Pranjul Yadav; Khoa D. Doan; S. Sathiya Keerthi (IEEE BigData, 2019)

Domain adaptation in display advertising: an application for partner cold-start. - Karan Aggarwal; Pranjul Yadav; S. Sathiya Keerthi (RecSys, 2019)

An Empirical Analysis of Deep Learning for Cardinality Estimation. - Jennifer Ortiz; Magdalena Balazinska; Johannes Gehrke; S. Sathiya Keerthi (CoRR, 2019)

Regression with Conditional GAN. - Karan Aggarwal; Matthieu Kirchmeyer; Pranjul Yadav; S. Sathiya Keerthi; Patrick Gallinari (CoRR, 2019)

Regression via Implicit Models and Optimal Transport Cost Minimization. - Saurav Manchanda; Khoa D. Doan; Pranjul Yadav; S. Sathiya Keerthi (CoRR, 2020)

Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space. - Khoa D. Doan; Saurav Manchanda; Fengjiao Wang; S. Sathiya Keerthi; Avradeep Bhowmik; Chandan K. Reddy (CoRR, 2020)

Efficient Algorithms for Global Inference in Internet Marketplaces. - Rohan Ramanath; S. Sathiya Keerthi; Yao Pan; Konstantin Salomatin; Kinjal Basu 001 (CoRR, 2021)

Logit Attenuating Weight Normalization. - Aman Gupta; Rohan Ramanath; Jun Shi; Anika Ramachandran; Sirou Zhou; Mingzhou Zhou; S. Sathiya Keerthi (CoRR, 2021)

Efficient Vertex-Oriented Polytopic Projection for Web-Scale Applications. - Rohan Ramanath; S. Sathiya Keerthi; Yao Pan; Konstantin Salomatin; Kinjal Basu 001 (AAAI, 2022)

Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization. - Kayhan Behdin; Qingquan Song; Aman Gupta; David Durfee; Ayan Acharya; S. Sathiya Keerthi; Rahul Mazumder (CoRR, 2022)

Optimizing for Member Value in an Edge Building Marketplace. - Ayan Acharya; Siyuan Gao; Ankan Saha; Borja Ocejo; Kinjal Basu 001; Sathiya Keerthi Selvaraj; Rahul Mazumder; Aman Gupta; Parag Agrawal (CIKM, 2023)

Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference. - Aman Gupta; S. Sathiya Keerthi; Ayan Acharya; Miao Cheng; Borja Ocejo Elizondo; Rohan Ramanath; Rahul Mazumder; Kinjal Basu 001; J. Kenneth Tay; Rupesh Gupta (KDD, 2023)

Promoting Inactive Members in Edge-Building Marketplace. - Ayan Acharya; Siyuan Gao; Borja Ocejo; Kinjal Basu 001; Ankan Saha; Sathiya Keerthi Selvaraj; Rahul Mazumder; Parag Agrawal; Aman Gupta (WWW (Companion Volume), 2023)

mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization. - Kayhan Behdin; Qingquan Song; Aman Gupta; Ayan Acharya; David Durfee; Borja Ocejo; S. Sathiya Keerthi; Rahul Mazumder (CoRR, 2023)

QuantEase: Optimization-based Quantization for Language Models - An Efficient and Intuitive Algorithm. - Kayhan Behdin; Ayan Acharya; Aman Gupta; Sathiya Keerthi Selvaraj; Rahul Mazumder (CoRR, 2023)

A Precise Characterization of SGD Stability Using Loss Surface Geometry. - Gregory Dexter; Borja Ocejo; S. Sathiya Keerthi; Aman Gupta; Ayan Acharya; Rajiv Khanna (ICLR, 2024)

LiRank: Industrial Large Scale Ranking Models at LinkedIn. - Fedor Borisyuk; Mingzhou Zhou; Qingquan Song; Siyu Zhu; Birjodh Tiwana; Ganesh Parameswaran; Siddharth Dangi; Lars Hertel; Qiang Charles Xiao; Xiaochen Hou; Yunbo Ouyang; Aman Gupta; et al. (KDD, 2024)

LiMAML: Personalization of Deep Recommender Models via Meta Learning. - Ruofan Wang; Prakruthi Prabhakar; Gaurav Srivastava 001; Tianqi Wang; Zeinab S. Jalali; Varun Bharill; Yunbo Ouyang; Aastha Nigam; Divya Venugopalan; Aman Gupta; Fedor Borisyuk; S. Sathiya Keerthi; et al. (KDD, 2024)

Neural Optimization with Adaptive Heuristics for Intelligent Marketing System. - Changshuai Wei; Benjamin Zelditch; Joyce Chen; Andre Assuncao Silva T. Ribeiro; Jingyi Kenneth Tay; Borja Ocejo Elizondo; Sathiya Keerthi Selvaraj; Aman Gupta; Licurgo Benemann De Almeida (KDD, 2024)

FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference. - Zirui Liu 001; Qingquan Song; Qiang Charles Xiao; Sathiya Keerthi Selvaraj; Rahul Mazumder; Aman Gupta; Xia Hu 001 (CoRR, 2024)

AlphaPO - Reward shape matters for LLM alignment. - Aman Gupta; Shao Tang; Qingquan Song; Sirou Zhu; Jiwoo Hong; Ankan Saha; Viral Gupta; Noah Lee; Eunki Kim; Jason Zhu; Natesh Pillai; S. Sathiya Keerthi (CoRR, 2025)