Aritra Ghosh

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 29

Top Topics

Risk Minimization

Computerized Adaptive Testing

Decision Tree Learning

Top Venues

Publications

Nischal Ashok Kumar, Wanyong Feng, Jaewook Lee, Hunter McNichols, Aritra Ghosh, Andrew S. Lan
A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing. EDM (2023)
Wanyong Feng, Aritra Ghosh, Stephen Sireci, Andrew S. Lan
Balancing Test Accuracy and Security in Computerized Adaptive Testing. AIED (2023)
Aritra Ghosh, Andrew S. Lan
DiFA: Differentiable Feature Acquisition. AAAI (2023)
Wanyong Feng, Aritra Ghosh, Stephen Sireci, Andrew S. Lan
Balancing Test Accuracy and Security in Computerized Adaptive Testing. CoRR (2023)
Aritra Ghosh, Saayan Mitra, Andrew S. Lan
DiPS: Differentiable Policy for Sketching in Recommender Systems. AAAI (2022)
Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan
Automated Scoring for Reading Comprehension via In-context BERT Tuning. AIED (1) (2022)
Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan
Automated Scoring for Reading Comprehension via In-context BERT Tuning. CoRR (2022)
Aritra Ghosh, Andrew S. Lan
Do We Really Need Gold Samples for Sample Weighting Under Label Noise? CoRR (2021)
Aritra Ghosh, Andrew S. Lan
BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing. CoRR (2021)
Aritra Ghosh, Andrew S. Lan
Contrastive Learning Improves Model Robustness Under Label Noise. CVPR Workshops (2021)
Aritra Ghosh, Andrew S. Lan
Do We Really Need Gold Samples for Sample Weighting under Label Noise? WACV (2021)
Aritra Ghosh, Andrew S. Lan
BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing. IJCAI (2021)
Aritra Ghosh, Jay Raspat, Andrew S. Lan
Option Tracing: Beyond Correctness Analysis in Knowledge Tracing. CoRR (2021)
Aritra Ghosh, Andrew S. Lan
Contrastive Learning Improves Model Robustness Under Label Noise. CoRR (2021)
Aritra Ghosh, Saayan Mitra, Andrew S. Lan
DiPS: Differentiable Policy for Sketching in Recommender Systems. CoRR (2021)
Aritra Ghosh, Jay Raspat, Andrew S. Lan
Option Tracing: Beyond Correctness Analysis in Knowledge Tracing. AIED (1) (2021)
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Viswanathan Swaminathan
Optimal Bidding Strategy without Exploration in Real-time Bidding. SDM (2020)
Aritra Ghosh, Beverly Park Woolf, Shlomo Zilberstein, Andrew S. Lan
Skill-based Career Path Modeling and Recommendation. IEEE BigData (2020)
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Viswanathan Swaminathan
Optimal Bidding Strategy without Exploration in Real-time Bidding. CoRR (2020)
Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan
Context-Aware Attentive Knowledge Tracing. KDD (2020)
Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan
Context-Aware Attentive Knowledge Tracing. CoRR (2020)
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, Viswanathan Swaminathan
Scalable Bid Landscape Forecasting in Real-time Bidding. CoRR (2020)
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, Viswanathan Swaminathan
Scalable Bid Landscape Forecasting in Real-Time Bidding. ECML/PKDD (3) (2019)
Aritra Ghosh, Himanshu Kumar, P. S. Sastry
Robust Loss Functions under Label Noise for Deep Neural Networks. AAAI (2017)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
On the Robustness of Decision Tree Learning Under Label Noise. PAKDD (1) (2017)
Aritra Ghosh, Himanshu Kumar, P. S. Sastry
Robust Loss Functions under Label Noise for Deep Neural Networks. CoRR (2017)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
On the Robustness of Decision Tree Learning under Label Noise. CoRR (2016)
Aritra Ghosh, Dinesh Gaurav, Rahul Agrawal
A Preference Approach to Reputation in Sponsored Search. CIKM (2016)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
Making risk minimization tolerant to label noise. Neurocomputing 160 (2015)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
Making Risk Minimization Tolerant to Label Noise. CoRR (2014)