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Joydeep Ghosh

35 papers · 2002–2024 · 8 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (22) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (14) πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🌱 Topic Pioneer πŸ† Keyword Champion (2) 🧬 Topic Evolution πŸ‘₯ Mega-Team (25) πŸ’Ž Century Club (35) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (67) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (12)

Conferences

AISTATS (14) NIPS (7) JMLR (5) ICML (4) IJCAI (2) ACL (1) EMNLP (1) IJCNLP (1)

Top co-authors

Rajiv Khanna (7) Oluwasanmi Koyejo (6) Arindam Banerjee (4) Xing Han (3) Diego Garcia-Olano (3) Russell Poldrack (3) Avradeep Bhowmik (3) nhαΊ­t Hα»“ (3) Byron Wallace (3) Yasumasa Onoe (3)

Keywords

submodular optimization (4) aggregated datum (3) matrix completion (3) bayesian inference (3) greedy algorithm (2) neuroimaging datum (2) information projection (2) bregman divergence (2) gamma process (2) exponential family (2) low-rank matrix (2) restricted strong convexity (2) generalized linear model (2) nonparametric bayesian (2) feature selection (2) approximate inference (2) convex optimization (2) variational inference (2) federated learning (2) model interpretability (2)

Papers

SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors NIPS 2024
A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings NIPS 2024
Designing Robust Transformers using Robust Kernel Density Estimation NIPS 2023
FEAMOE: Fair, Explainable and Adaptive Mixture of Experts IJCAI 2023
Intermediate Entity-based Sparse Interpretable Representation Learning EMNLP 2022
Architecture Agnostic Federated Learning for Neural Networks ICML 2022
Biomedical Interpretable Entity Representations ACL 2021
Biomedical Interpretable Entity Representations IJCNLP 2021
Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series AISTATS 2021
Certifai: A Toolkit for Building Trust in AI Systems IJCAI 2020
On Single Source Robustness in Deep Fusion Models NIPS 2019
Interpreting Black Box Predictions using Fisher Kernels AISTATS 2019
Boosting Variational Inference: an Optimization Perspective AISTATS 2018
Nonparametric Bayesian sparse graph linear dynamical systems AISTATS 2018
Scalable Greedy Feature Selection via Weak Submodularity AISTATS 2017
Frequency Domain Predictive Modelling with Aggregated Data AISTATS 2017
Information Projection and Approximate Inference for Structured Sparse Variables AISTATS 2017
On Approximation Guarantees for Greedy Low Rank Optimization ICML 2017
Sparse Parameter Recovery from Aggregated Data ICML 2016
Preference Completion from Partial Rankings NIPS 2016
Generalized Linear Models for Aggregated Data AISTATS 2015
Parameter Estimation of Generalized Linear Models without Assuming their Link Function AISTATS 2015
Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices AISTATS 2015
Unified View of Matrix Completion under General Structural Constraints NIPS 2015
Sparse Submodular Probabilistic PCA AISTATS 2015
On Prior Distributions and Approximate Inference for Structured Variables NIPS 2014
LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series AISTATS 2014
Exponential Family Matrix Completion under Structural Constraints ICML 2014
DYNACARE: Dynamic Cardiac Arrest Risk Estimation AISTATS 2013
Bayesian Structure Learning for Functional Neuroimaging AISTATS 2013
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation JMLR 2007
Clustering with Bregman Divergences JMLR 2005
Clustering on the Unit Hypersphere using von Mises-Fisher Distributions JMLR 2005
A Unified Framework for Model-based Clustering JMLR 2003
Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions JMLR 2002