Chiranjib Bhattacharyya

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

Achievements

+15 more ↓

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🌍 Conference Polyglot (11)

🗺️ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (8) 🏆 Grand Slam 🧬 Topic Evolution 🌱 Topic Pioneer 🔬 Deep Specialist (10) 🏆 Keyword Champion (5) ❓ The Questioner 🚀 Conference Pioneer 💎 Century Club (38) 🗃️ Keyword Collector (176) 🔥 Unstoppable (9) 📈 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 Lovász ϑ 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