Sunil Gupta

Orcid: 0000-0002-3308-1930

Affiliations:
  • Deakin University, Center for Pattern Recognition and Data Analytics, Australia


According to our database1, Sunil Gupta authored at least 173 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Generating Realistic Tabular Data with Large Language Models.
CoRR, 2024

Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning.
CoRR, 2024

Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior.
CoRR, 2024

Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime.
CoRR, 2024

Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Improving Diversity in Black-Box Few-Shot Knowledge Distillation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

PINN-BO: A Black-Box Optimization Algorithm Using Physics-Informed Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

EMOTE: An Explainable Architecture for Modelling the Other through Empathy.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Policy Learning for Off-Dynamics RL with Deficient Support.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Root Cause Explanation of Outliers under Noisy Mechanisms.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Balanced Q-learning: Combining the influence of optimistic and pessimistic targets.
Artif. Intell., December, 2023

NeuralBO: A black-box optimization algorithm using deep neural networks.
Neurocomputing, November, 2023

Unified Multi-Weather Visibility Restoration.
IEEE Trans. Multim., 2023

LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying.
CoRR, 2023

Predictive Modeling through Hyper-Bayesian Optimization.
CoRR, 2023

BO-Muse: A human expert and AI teaming framework for accelerated experimental design.
CoRR, 2023

Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks.
CoRR, 2023

Gradient Descent in Neural Networks as Sequential Learning in RKBS.
CoRR, 2023

Guiding Visual Question Answering with Attention Priors.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Continual Learning with Dependency Preserving Hypernetworks.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space.
Proceedings of the International Conference on Machine Learning, 2023

Multi-weather Image Restoration via Domain Translation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Domain Generalization with Interpolation Robustness.
Proceedings of the Asian Conference on Machine Learning, 2023

Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee.
Proceedings of the Asian Conference on Machine Learning, 2023

On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces.
Trans. Mach. Learn. Res., 2022

Dual-frame spatio-temporal feature modulation for video enhancement.
Pattern Recognit., 2022

Verification of integrity of deployed deep learning models using Bayesian Optimization.
Knowl. Based Syst., 2022

Prescriptive analytics with differential privacy.
Int. J. Data Sci. Anal., 2022

Defense Against Multi-target Trojan Attacks.
CoRR, 2022

Memory-Constrained Policy Optimization.
CoRR, 2022

Real-Time Skill Discovery in Intelligent Virtual Assistants.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Expected Improvement for Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning to Constrain Policy Optimization with Virtual Trust Region.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Semantic Control of Generative Musical Attributes.
Proceedings of the 23rd International Society for Music Information Retrieval Conference, 2022

Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions.
Proceedings of the Computer Vision - ECCV 2022, 2022

Black-Box Few-Shot Knowledge Distillation.
Proceedings of the Computer Vision - ECCV 2022, 2022

Sympathy-based Reinforcement Learning Agents.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

TRF: Learning Kernels with Tuned Random Features.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
An Unified Recurrent Video Object Segmentation Framework for Various Surveillance Environments.
IEEE Trans. Image Process., 2021

Adaptive cost-aware Bayesian optimization.
Knowl. Based Syst., 2021

Fairness improvement for black-box classifiers with Gaussian process.
Inf. Sci., 2021

Semantic Host-free Trojan Attack.
CoRR, 2021

A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research.
CoRR, 2021

Plug and Play, Model-Based Reinforcement Learning.
CoRR, 2021

Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support.
CoRR, 2021

ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms.
CoRR, 2021

On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks.
CoRR, 2021

Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient.
BioData Min., 2021

Fast Conditional Network Compression Using Bayesian HyperNetworks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Variational Hyper-encoding Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Knowledge Distillation with Distribution Mismatch.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Sparse Spectrum Gaussian Process for Bayesian Optimization.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Kernel Functional Optimisation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bayesian Optimistic Optimisation with Exponentially Decaying Regret.
Proceedings of the 38th International Conference on Machine Learning, 2021

A New Representation of Successor Features for Transfer across Dissimilar Environments.
Proceedings of the 38th International Conference on Machine Learning, 2021

Distributional Reinforcement Learning via Moment Matching.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

High Dimensional Level Set Estimation with Bayesian Neural Network.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Bayesian strategy selection identifies optimal solutions to complex problems using an example from GP prescribing.
npj Digit. Medicine, 2020

Incorporating expert prior in Bayesian optimisation via space warping.
Knowl. Based Syst., 2020

Fast hyperparameter tuning using Bayesian optimization with directional derivatives.
Knowl. Based Syst., 2020

Batch Bayesian optimization using multi-scale search.
Knowl. Based Syst., 2020

Bayesian optimisation in unknown bounded search domains.
Knowl. Based Syst., 2020

Logically Consistent Loss for Visual Question Answering.
CoRR, 2020

Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition.
CoRR, 2020

Distributional Reinforcement Learning with Maximum Mean Discrepancy.
CoRR, 2020

HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network.
CoRR, 2020

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling.
CoRR, 2020

Bayesian Optimization for Adaptive Experimental Design: A Review.
IEEE Access, 2020

Unsupervised Anomaly Detection on Temporal Multiway Data.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Bayesian Optimization with Missing Inputs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Scalable Backdoor Detection in Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Level Set Estimation with Search Space Warping.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

DeepCoDA: personalized interpretability for compositional health data.
Proceedings of the 37th International Conference on Machine Learning, 2020

Accelerated Bayesian Optimisation through Weight-Prior Tuning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Distributionally Robust Bayesian Quadrature Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Bayesian Optimization for Categorical and Category-Specific Continuous Inputs.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Filtering Bayesian optimization approach in weakly specified search space.
Knowl. Inf. Syst., 2019

A flexible transfer learning framework for Bayesian optimization with convergence guarantee.
Expert Syst. Appl., 2019

Cost-aware Multi-objective Bayesian optimisation.
CoRR, 2019

Sparse Spectrum Gaussian Process for Bayesian Optimisation.
CoRR, 2019

Stable Bayesian Optimisation via Direct Stability Quantification.
CoRR, 2019

Incomplete Conditional Density Estimation for Fast Materials Discovery.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Explaining Black-Box Models Using Interpretable Surrogates.
Proceedings of the PRICAI 2019: Trends in Artificial Intelligence, 2019

Bayesian Optimization with Unknown Search Space.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Multi-objective Bayesian optimisation with preferences over objectives.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Information-Theoretic Multi-task Learning Framework for Bayesian Optimisation.
Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

Bayesian Optimization with Discrete Variables.
Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

Detection of Compromised Models Using Bayesian Optimization.
Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

Bayesian Optimisation for Objective Functions with Varying Smoothness.
Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

Bayesian Functional Optimisation with Shape Prior.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Stable Bayesian optimization.
Int. J. Data Sci. Anal., 2018

Hybrid Generative-Discriminative Models for Inverse Materials Design.
CoRR, 2018

Practical Batch Bayesian Optimization for Less Expensive Functions.
CoRR, 2018

Kernel Pre-Training in Feature Space via m-Kernels.
CoRR, 2018

Multi-Target Optimisation via Bayesian Optimisation and Linear Programming.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Efficient Bayesian Optimisation Using Derivative Meta-model.
Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

Selecting Optimal Source for Transfer Learning in Bayesian Optimisation.
Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

Information-Theoretic Transfer Learning Framework for Bayesian Optimisation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Exploration Enhanced Expected Improvement for Bayesian Optimization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

A Privacy Preserving Bayesian Optimization with High Efficiency.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Prescriptive Analytics Through Constrained Bayesian Optimization.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Expected Hypervolume Improvement with Constraints.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

Differentially Private Prescriptive Analytics.
Proceedings of the IEEE International Conference on Data Mining, 2018

Accelerating Experimental Design by Incorporating Experimenter Hunches.
Proceedings of the IEEE International Conference on Data Mining, 2018

Sparse Approximation for Gaussian Process with Derivative Observations.
Proceedings of the AI 2018: Advances in Artificial Intelligence, 2018

Exploiting Strategy-Space Diversity for Batch Bayesian Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
A Framework for Mixed-Type Multioutcome Prediction With Applications in Healthcare.
IEEE J. Biomed. Health Informatics, 2017

Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data.
Knowl. Inf. Syst., 2017

Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions.
Knowl. Inf. Syst., 2017

Low overhead octet indexed template security scheme for multi-modal biometric system.
J. Intell. Fuzzy Syst., 2017

Budgeted Batch Bayesian Optimization With Unknown Batch Sizes.
CoRR, 2017

Process-constrained batch Bayesian optimisation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

High Dimensional Bayesian Optimization using Dropout.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

High Dimensional Bayesian Optimization with Elastic Gaussian Process.
Proceedings of the 34th International Conference on Machine Learning, 2017

Bayesian Optimization in Weakly Specified Search Space.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Regret Bounds for Transfer Learning in Bayesian Optimisation.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Regret for Expected Improvement over the Best-Observed Value and Stopping Condition.
Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016
Nonparametric discovery of movement patterns from accelerometer signals.
Pattern Recognit. Lett., 2016

Modelling multilevel data in multimedia: A hierarchical factor analysis approach.
Multim. Tools Appl., 2016

Multiple task transfer learning with small sample sizes.
Knowl. Inf. Syst., 2016

A new transfer learning framework with application to model-agnostic multi-task learning.
Knowl. Inf. Syst., 2016

Stabilizing l<sub>1</sub>-norm prediction models by supervised feature grouping.
J. Biomed. Informatics, 2016

Privacy Aware K-Means Clustering with High Utility.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Flexible Transfer Learning Framework for Bayesian Optimisation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Differentially Private Multi-task Learning.
Proceedings of the Intelligence and Security Informatics - 11th Pacific Asia Workshop, 2016

Bayesian nonparametric Multiple Instance Regression.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Transfer learning for rare cancer problems via Discriminative Sparse Gaussian Graphical model.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Multiple adverse effects prediction in longitudinal cancer treatment.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Stable clinical prediction using graph support vector machines.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Hyperparameter tuning for big data using Bayesian optimisation.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Budgeted Batch Bayesian Optimization.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Cascade Bayesian Optimization.
Proceedings of the AI 2016: Advances in Artificial Intelligence, 2016

Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning.
Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016

Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media.
Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016

A Bayesian Nonparametric Approach for Multi-label Classification.
Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015
A predictive framework for modeling healthcare data with evolving clinical interventions.
Stat. Anal. Data Min., 2015

Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso.
J. Biomed. Informatics, 2015

What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Prediciton of Emergency Events: A Multi-Task Multi-Label Learning Approach.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Differentially Private Random Forest with High Utility.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Improved risk predictions via sparse imputation of patient conditions in electronic medical records.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Exploiting feature relationships towards stable feature selection.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Stable Feature Selection with Support Vector Machines.
Proceedings of the AI 2015: Advances in Artificial Intelligence, 2015

2014
A framework for feature extraction from hospital medical data with applications in risk prediction.
BMC Bioinform., 2014

Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Fixed-lag particle filter for continuous context discovery using Indian Buffet Process.
Proceedings of the IEEE International Conference on Pervasive Computing and Communications, 2014

Intervention-Driven Predictive Framework for Modeling Healthcare Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2014

A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

2013
Connectivity, Online Social Capital, and Mood: A Bayesian Nonparametric Analysis.
IEEE Trans. Multim., 2013

Regularized nonnegative shared subspace learning.
Data Min. Knowl. Discov., 2013

Extraction of latent patterns and contexts from social honest signals using hierarchical Dirichlet processes.
Proceedings of the 2013 IEEE International Conference on Pervasive Computing and Communications, 2013

Interactive browsing system for anomaly video surveillance.
Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, 2013

Factorial Multi-Task Learning : A Bayesian Nonparametric Approach.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

A Bayesian Nonparametric Joint Factor Model for Learning Shared and Individual Subspaces from Multiple Data Sources.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

A nonparametric Bayesian Poisson gamma model for count data.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

2011
A Bayesian Framework for Learning Shared and Individual Subspaces from Multiple Data Sources.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

2010
Nonnegative shared subspace learning and its application to social media retrieval.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2008
Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition.
Proceedings of the Sixth Indian Conference on Computer Vision, Graphics & Image Processing, 2008


  Loading...