| 2025 | CVPR | Pseudo-labelling meets Label Smoothing for Noisy Partial Label Learning. | Darshana Saravanan, Naresh Manwani, Vineet Gandhi |
| 2025 | PAKDD | Achieving Fair PCA Using Joint Eigenvalue Decomposition. | Vidhi Rathore, Naresh Manwani |
| 2024 | ACML | Towards Calibrated Losses for Adversarial Robust Reject Option Classification. | Vrund Shah, Tejas Kiran Chaudhari, Naresh Manwani |
| 2024 | COMAD | Text Representation Models based on the Spatial Distributional Properties of Word Embeddings. | Narendra Babu Unnam, Krishna Reddy Polepalli, Amit Pandey, Naresh Manwani |
| 2024 | PRICAI | EQUISCALE: Equitable Scaling for Abstention Learning. | Tejas Kiran Chaudhari, Naresh Manwani |
| 2023 | ICAART | Features Normalisation and Standardisation (FNS): An Unsupervised Approach for Detecting Adversarial Attacks for Medical Images. | Sreenivasan Mohandas, Naresh Manwani |
| 2023 | IJCNN | Delaytron: Efficient Learning of Multiclass Classifiers with Delayed Bandit Feedbacks. | Naresh Manwani, Mudit Agarwal |
| 2023 | PRICAI | CDAN: Cost Dependent Deep Abstention Network. | Bhavya Kalra, Naresh Manwani |
| 2023 | PRICAI | RPL-SVM: Making SVM Robust Against Missing Values and Partial Labels. | Sreenivasan Mohandas, Naresh Manwani |
| 2022 | ACML | RoLNiP: Robust Learning Using Noisy Pairwise Comparisons. | Samartha S. Maheshwara, Naresh Manwani |
| 2022 | ICAART | Momentum Iterative Gradient Sign Method Outperforms PGD Attacks. | Sreenivasan Mohandas, Naresh Manwani, Durga Prasad Dhulipudi |
| 2022 | KDD | Advances in Exploratory Data Analysis, Visualisation and Quality for Data Centric AI Systems. | Hima Patel, Shanmukha C. Guttula, Ruhi Sharma Mittal, Naresh Manwani, Laure Berti-quille, Abhijit Manatkar |
| 2022 | PAKDD | ALBIF: Active Learning with BandIt Feedbacks. | Mudit Agarwal, Naresh Manwani |
| 2022 | SSDBM | Journey to the center of the words: Word weighting scheme based on the geometry of word embeddings. | Narendra Babu Unnam, P. Krishna Reddy, Amit Pandey, Naresh Manwani |
| 2021 | COMAD | Exact Passive Aggressive Algorithm for Multiclass Classification Using Partial Labels. | Maanik Arora, Naresh Manwani |
| 2021 | PAKDD | Learning Multiclass Classifier Under Noisy Bandit Feedback. | Mudit Agarwal, Naresh Manwani |
| 2021 | PAKDD | Cooperative Monitoring of Malicious Activity in Stock Exchanges. | Bhavya Kalra, Sai Krishna Munnangi, Kushal Majmundar, Naresh Manwani, Praveen Paruchuri |
| 2021 | PRICAI | Multiclass Classification Using Dilute Bandit Feedback. | Gaurav Batra, Naresh Manwani |
| 2021 | UAI | RISAN: Robust instance specific deep abstention network. | Bhavya Kalra, Kulin Shah, Naresh Manwani |
| 2020 | AAAI | Online Active Learning of Reject Option Classifiers. | Kulin Shah, Naresh Manwani |
| 2020 | ACML | Exact Passive-Aggressive Algorithms for Multiclass Classification Using Bandit Feedbacks. | Maanik Arora, Naresh Manwani |
| 2020 | ACML | Robust Deep Ordinal Regression under Label Noise. | Bhanu Garg, Naresh Manwani |
| 2020 | COMAD | Robust Learning of Multi-Label Classifiers under Label Noise. | Himanshu Kumar, Naresh Manwani, P. S. Sastry |
| 2020 | PAKDD | Online Algorithms for Multiclass Classification Using Partial Labels. | Rajarshi Bhattacharjee, Naresh Manwani |
| 2019 | AAAI | Sparse Reject Option Classifier Using Successive Linear Programming. | Kulin Shah, Naresh Manwani |
| 2019 | COMAD | PRIL: Perceptron Ranking Using Interval Labels. | Naresh Manwani |
| 2018 | ICONIP | fMRI Semantic Category Decoding Using Linguistic Encoding of Word Embeddings. | Subba Reddy Oota, Naresh Manwani, Raju S. Bapi |
| 2017 | PAKDD | On the Robustness of Decision Tree Learning Under Label Noise. | Aritra Ghosh, Naresh Manwani, P. S. Sastry |
| 2015 | PAKDD | Double Ramp Loss Based Reject Option Classifier. | Naresh Manwani, Kalpit Desai, Sanand Sasidharan, Ramasubramanian Sundararajan |