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27th COMAD / 9th CODS 2022: Bangalore, India
- Gargi Dasgupta, Yogesh Simmhan, Balaji Vasan Srinivasan, Sourav Bhowmick, Amith Singhee, Maya Ramanath, Nipun Batra, Abhinandan S. Prasad:
CODS-COMAD 2022: 5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD), Bangalore, India, January 8 - 10, 2022. ACM 2022, ISBN 978-1-4503-8582-4
Research Track - Data Management
- Sai Kiran Narayanaswami, Nandan Sudarsanam, Balaraman Ravindran:
An Active Learning Framework for Efficient Robust Policy Search. 1-9 - Geetika Arora, Shantanu Vichare, Kamlesh Tiwari:
IrisIndexNet: Indexing on Iris Databases for Faster Identification. 10-18
Research Track - Information Extraction
- Govind Krishnan Gangadhar, Ashish Kulkarni:
Extraction of Product Specifications from the Web - Going Beyond Tables and Lists. 19-27 - Ritvik Vij, Rohit Raj, Madhur Singhal, Manish Tanwar, Srikanta Bedathur:
VizAI : Selecting Accurate Visualizations of Numerical Data. 28-36
Research Track - Learning & Optimization
- Debojyoti Dey, Bhaskar Mukhoty, Purushottam Kar:
AGGLIO: Global Optimization for Locally Convex Functions. 37-45 - Yuan-Chi Chang, Dharmashankar Subramanian, Raju Pavuluri, Timothy Dinger:
Time Series Representation Learning with Contrastive Triplet Selection. 46-53 - Jayadev Naram
, Tanmay Kumar Sinha, Pawan Kumar:
A Riemannian Approach to Extreme Classification Problems. 54-62 - Sapana Chaudhary, Balaraman Ravindran:
Smooth Imitation Learning via Smooth Costs and Smooth Policies. 63-71 - Sandesh Kamath, Amit Deshpande, K. V. Subrahmanyam, Vineeth N. Balasubramanian:
Universalization of Any Adversarial Attack using Very Few Test Examples. 72-80
Research Track - ML for Education
- Omkar Shelke, Hardik Meisheri, Harshad Khadilkar:
Identifying efficient curricula for reinforcement learning in complex environments with a fixed computational budget. 81-89 - Anubha Kabra
Evaluation Toolkit For Robustness Testing Of Automatic Essay Scoring Systems. 90-99
Research Track (Short Papers) - Data Management
- Athul M. A, Arun Rajkumar:
Hyper-IMRANK: Ranking-based Influence Maximization for Hypergraphs. 100-104
Research Track (Short Papers) - Information Extraction
- Rosario Uceda-Sosa, Nandana Mihindukulasooriya
Domain specific ontologies from Linked Open Data (LOD). 105-109
Research Track (Short Papers) - Learning & Optimization
- Diptikalyan Saha, Aniya Aggarwal, Sandeep Hans:
Data Synthesis for Testing Black-Box Machine Learning Models. 110-114
Research Track (Short Papers) - Natural Language Processing
- Dwaipayan Roy
Local or Global? A Comparative Study on Applications of Embedding Models for Information Retrieval. 115-119 - Neelamadhav Gantayat, Prateeti Mohapatra:
Using Semantic Role Knowledge for Relevance Ranking of Key Phrases in Documents: An Unsupervised Approach. 120-124 - Sourya Dipta Das, Ayan Basak, Soumil Mandal, Dipankar Das:
AdvCodeMix: Adversarial Attack on Code-Mixed Data. 125-129 - Abhinav Nagpal
Fine Grained Classification of Personal Data Entities with Language Models. 130-134
Applied Data Science Track - Natural Language Processing
- Vini Dixit:
GCFI++: Embedding and Frequent Itemset based Incremental Hierarchical Clustering with Labels and Outliers. 135-143 - Sumanth Prabhu, Aditya Kiran Brahma, Hemant Misra
Customer Support Chat Intent Classification using Weak Supervision and Data Augmentation. 144-152
Applied Data Science Track - Prediction
- Gaurav Pawar, Abhinav Ganesan, Ritwik Prashant Moghe, Bharath Nayak, Tanya Khanna, Kranthi Mitra Adusimilli:
Learning to Predict Two-Wheeler Travel Distance. 153-161 - Sruthikeerthi Nandita, Goutham Zampani, Gokul S. Krishnan, Gitakrishnan Ramadurai
Automated Incident Location Identification for EMS from Ambulance Geospatial Data. 162-168
Applied Data Science Track - Recommender Systems
- Rohan Saxena, Maheep Chaudhary, Chandresh Kumar Maurya, Shitala Prasad:
An Intelligent Recommendation-cum-Reminder System. 169-177 - Rutvik Vijjali, Deepesh Bhageria, Ashay Tamhane, Mithun T. M, Jairaj Sathyanarayana:
FoodNet: Simplifying Online Food Ordering with Contextual Food Combos. 178-185 - Koyel Mukherjee, Deepanshi Seth, Prachi Mittal, Nuthi S. Gowtham, Tridib Mukherjee, Dattatreya Biswas, Sanjay Agrawal:
ComParE: A User Behavior Centric Framework for Personalized Recommendations in Skill Gaming Platforms. 186-194
Applied Data Science Track - Time Series
- Ayush Jain
Towards Context-based Model Selection for Improved Crop Price Forecasting. 195-203
Applied Data Science Track - Vision and Video
- Varad Srivastava
Diagnosing Covid-19 using AI based Medical Image Analysis. 204-212 - Ishaan Lodha, Lakshana Kolur, Keerthan Krishnan, Kumar Dheenadayalan, Dinkar Sitaram, Siddhartha Nandi:
Cost-Optimized Video Transfer using Real-Time Super Resolution Convolutional Neural Networks. 213-221
Applied Data Science Track (Short Papers) - Generative Models
- Hetvi Shastri, Dhruvi Lodhavia
Vastr-GAN: Versatile Apparel Synthesised from Text using a Robust Generative Adversarial Network. 222-226
Applied Data Science Track (Short Papers) - Natural Language Processing
- Rohan Sukumaran, Sumanth Prabhu, Hemant Misra
Enhanced Text Classification using Proxy Labels and Knowledge Distillation. 227-230
Applied Data Science Track (Short Papers) - Network Analysis
- Madhav Agrawal, Shubham Sharma, Amit Anil Nanavati
Study of Equities using Signed Social Network. 231-235
Applied Data Science Track (Short Papers) - Reinforcement Learning
- Abhinav Gupta, Supratim Ghosh, Anulekha Dhara:
Deep Reinforcement Learning Algorithm for Fast Solutions to Vehicle Routing Problem with Time-Windows. 236-240
Applied Data Science Track (Short Papers) - Vision and Video
- Rohit Ramaprasad, Sundaresan Raman
SEMFD-Net : A Stacked Ensemble for Multiple Foliar Disease Classification. 241-245
Demonstration Track
- Aparna Lalingkar, Parithimalan Arulchelvan, Advait Lonkar, Prakhar Mishra
Discussion Forum Analyzer: A tool for finding the quality of affirmation and identifying points of intervention in an academic discussion forum. 246-249 - Saravanan Krishnan, Alex Mathai, Amith Singhee, Atul Kumar, Shivali Agarwal, Keerthi Narayan Raghunath, David Wenk:
Incremental Analysis of Legacy Applications Using Knowledge Graphs for Application Modernization. 250-254 - Jathin Badam, Akash Bonagiri
Aletheia: A Fake News Detection System for Hindi. 255-259 - Debopriyo Banerjee, Harsh Maheshwari, Lucky Dhakad, Arnab Bhattacharya, Niloy Ganguly, Muthusamy Chelliah, Suyash Agarwal:
An Application to Generate Style Guided Compatible Outfit. 260-264 - Haricharan Aragonda, Karimulla Shaik, Harshit Jain, Samir Shah:
Accurate and Real Time Assisted Cataloging in E-commerce using Dual Images. 265-269 - Viral Parekh, Surbhi Mathur, Soma Biswas, Karimulla Shaik:
VPER: Visual Product Entity Recognition for Fashion-wear. 270-274 - Kamal Kumar Gupta, Divya Kumari, Soumya Chennabasavaraj, Nikesh Garera, Asif Ekbal:
ReviewMT: Sentiment Preserved E-Commerce Review Translation System. 275-279
Young Researchers' Symposium
- Akshay Gupta, Biplav Srivastava:
Towards Developing Better Object Detectors for Real-World Use. 280-281 - Varun Sivashankar, Nikil Selvam:
Local Linearity and Double Descent in Catastrophic Overfitting. 282-283 - Sujan Reddy A, Akashdeep, Harshvardhan, Sowmya Kamath S.
Ensemble Learning Approach for Short-term Energy Consumption Prediction. 284-285 - Suresh Kumar, P. Sreenivasa Kumar:
Solving TC-type AWPs using external knowledge & learning. 286-287 - Arun Kumar Singh, Sushant Dave, Shresth Mehta, Prathosh A. P.:
A data driven approach for Sanskrit Derivative Nouns analysis. 288-289 - Guna Sekhar Gedela, Joe Bobby, Nirav Bhatt:
Chemistry Inspired Molecular Representation for Property Prediction. 290-291 - C. Oswald, Gadi Jaya Sathwika, Arnab Bhattacharya:
Prediction of CardioVascular Disease (CVD) using Ensemble Learning Algorithms. 292-293 - Namasivayam Kalithasan
Making Fractional Distances work in the presence of White Noise - Motivation and Challenges. 294-295 - Shril Mody, Janvi Thakkar
Analysis of Image generation using Scene graphs. 296-297 - Samhita Kanaparthy, Manisha Padala, Sankarshan Damle
Fair Federated Learning for Heterogeneous Data. 298-299 - Saurabh Kumar, Nishant Sinha:
Probing TryOnGAN. 300-301 - Reshma Unnikrishnan, S. Sowmya Kamath
Population-centric Profiling with Social Data for Large-scale Epidemiological studies. 302-303 - Neel Patel
Towards Continuous Respiration Monitoring Using Mask. 304-305 - Athul Kumar, Aarchi Agrawal, K. S. Ashin Shanly
Image Caption Generator using Siamese Graph Convolutional Networks and LSTM. 306-307 - Abhishek Roy, Sandeep Kumar:
Network Enhancement using Spectral Properties. 308-309 - Harsh M. Patel, Praveen Venkatesh, Shivam Sahni, Varun Jain, Mrinal Anand, Mayank Singh:
Program Synthesis: Does Feedback Help? 310-311 - Lakshya A. Agrawal
A SPARQL to Cypher Transpiler: Proposal and Initial Results. 312-313 - Mauro Dalle Lucca Tosi
Convergence time analysis of Asynchronous Distributed Artificial Neural Networks. 314-315 - Amey Kulkarni, Devvrat Joshi:
Quantum Algorithm for Linear Regression for Large Feature-Set. 316-317 - Nayna Jain, Karthik Nandakumar, Nalini K. Ratha, Sharath Pankanti, Uttam Kumar:
PPDL - Privacy Preserving Deep Learning Using Homomorphic Encryption. 318-319 - Deeksha Aggarwal, Uttam Kumar, J. Senthilnath:
Towards Building a Flexible Online Learning Model for Data Stream Classification. 320-321 - Gaurav Viramgami, Hitarth Gandhi, Hrushti Naik, Nipun Mahajan, Praveen Venkatesh, Shivam Sahni, Mayank Singh:
Indian Classical Music Synthesis. 322-323 - Ankit Gupta, Aashu Khodwal, Nidhi Pal:
VacoPie: Visualizing Variance and Covariance Information onto Categorical Distribution of Data. 324-325 - Poorva Satish Bedmutha, Manas Satish Bedmutha
SciPred: An end to end approach to classify predatory journals. 326-327
Tutorials
- Vivek Srivastava, Mayank Singh:
Code-Mixed NLG: Resources, Metrics, and Challenges. 328-332 - Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang:
Uncertainty Quantification 360: A Hands-on Tutorial. 333-335 - Johnu George, Amit Saha:
End-to-end Machine Learning using Kubeflow. 336-338 - Mukta Paliwal, Dattaraj Rao, Amogh Kamat Tarcar:
Responsible AI Tutorial. 339-341 - Subhasis Banerjee, Aniruddha Panda, Saurabh Chawdhary, Pandu Devarakota:
Performance Engineering for Deep Learning Adaptation of Seismic Processing Workflow. 342-343 - Shantanu Sharma
Cryptographic Techniques for Data Processing. 344-347 - Hrishav Bakul Barua, Kartick Chandra Mondal, Sunirmal Khatua:
Green Computing for Big Data and Machine Learning. 348-351 - V. G. Vinod Vydiswaran, Xinyan Zhao, Deahan Yu:
Data Science and Natural Language Processing to Extract Information in Clinical Domain. 352-353 - Hima Patel, Nitin Gupta, Naveen Panwar, Ruhi Sharma Mittal, Sameep Mehta, Shanmukha C. Guttula, Shashank Mujumdar, Shazia Afzal, Srikanta Bedathur, Vitobha Munigala:
Automatic Assessment of Quality of your Data for AI. 354-357
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