← Authors

Chiranjib Bhattacharyya

38 papers · 2002–2025 · 11 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (11) 🌈 Renaissance Researcher (10) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (23) πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (8) πŸ† Grand Slam 🧬 Topic Evolution 🌱 Topic Pioneer πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (5) ❓ The Questioner πŸš€ Conference Pioneer πŸ’Ž Century Club (38) πŸ—ƒοΈ Keyword Collector (176) πŸ”₯ Unstoppable (9) πŸ“ˆ Trend Setter

Conferences

NIPS (11) ICML (7) JMLR (6) ICLR (4) AAAI (2) ACL (2) IJCAI (2) AISTATS (1) CVPR (1) EMNLP (1) UAI (1)

Top co-authors

Devdatt Dubhashi (6) Ravindran Kannan (4) Chaitanya Murti (4) Aharon Ben-tal (4) Vinay Jethava (3) Rakesh Shivanna (3) Anders Martinsson (2) Aadirupa Saha (2) Partha Talukdar (2) Tanay Narshana (2)

Keywords

convex optimization (7) support vector machine (6) multiple kernel learning (5) sample complexity (4) kernel methods (4) topic model (3) mirror descent (3) second order cone programming (3) orthonormal representation (3) robust optimization (2) semidefinite programming (2) admixture model (2) recurrent neural network (2) mirror descent algorithm (2) representation learning (2) mixed-norm regularization (2) latent dirichlet allocation (2) graph embedding (2) graph theory (2) combinatorial optimization (2)

Papers

CheXwhatsApp: A Dataset for Exploring Challenges in the Diagnosis of Chest X-rays through Mobile Devices CVPR 2025
LevAttention: Time, Space and Streaming Efficient Algorithm for Heavy Attentions ICLR 2025
LP-based Construction of DC Decompositions for Efficient Inference of Markov Random Fields AISTATS 2024
Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms NIPS 2024
DisCEdit: Model Editing by Identifying Discriminative Components NIPS 2024
TVSPrune - Pruning Non-discriminative filters via Total Variation separability of intermediate representations without fine tuning ICLR 2023
DFPC: Data flow driven pruning of coupled channels without data. ICLR 2023
Deep Recurrent Optimal Stopping NIPS 2023
When to Intervene: Learning Optimal Intervention Policies for Critical Events NIPS 2022
Finding k in Latent $k-$ polytope ICML 2021
Learning a Latent Simplex in Input Sparsity Time ICLR 2021
Dynamic to Static Lidar Scan Reconstruction Using Adversarially Trained Auto Encoder AAAI 2021
Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures ICML 2020
Learning With Subquadratic Regularization : A Primal-Dual Approach IJCAI 2020
Be Greedy: How Chromatic Number meets Regret Minimization in Graph Bandits UAI 2019
How Many Pairwise Preferences Do We Need to Rank a Graph Consistently? AAAI 2019
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks ACL 2019
Word2Sense: Sparse Interpretable Word Embeddings ACL 2019
Using Inherent Structures to design Lean 2-layer RBMs ICML 2018
RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information EMNLP 2018
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery ICML 2017
Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models ICML 2015
EntScene: Nonparametric Bayesian Temporal Segmentation of Videos Aimed at Entity-Driven Scene Detection IJCAI 2015
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization NIPS 2015
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction NIPS 2015
Global graph kernels using geometric embeddings ICML 2014
A provable SVD-based algorithm for learning topics in dominant admixture corpus NIPS 2014
Learning on graphs using Orthonormal Representation is Statistically Consistent NIPS 2014
Subtle Topic Models and Discovering Subtly Manifested Software Concerns Automatically ICML 2013
Lovasz theta function, SVMs and Finding Dense Subgraphs JMLR 2013
The LovΓ‘sz Ο‘ function, SVMs and finding large dense subgraphs NIPS 2012
Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices JMLR 2012
Variable Sparsity Kernel Learning JMLR 2011
Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions NIPS 2010
On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation NIPS 2009
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data JMLR 2006
Second Order Cone Programming Formulations for Feature Selection JMLR 2004
A Robust Minimax Approach to Classification JMLR 2002