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ORCIDMadalina Fiterau
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2020 – today
- 2025
[j3]Shalmali Joshi, Iñigo Urteaga, Wouter A. C. van Amsterdam, George Hripcsak, Pierre A. Elias
, Benjamin R. C. Amor, Noémie Elhadad, James C. Fackler, Mark P. Sendak, Jenna Wiens, Kaivalya Deshpande, Yoav Wald, Madalina Fiterau, Zachary C. Lipton, Daniel Malinsky, Madhur Nayan, Hongseok Namkoong, Soojin Park, Julia E. Vogt, Rajesh Ranganath:
AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation. J. Am. Medical Informatics Assoc. 32(3): 589-594 (2025)- [c23]Shiv Shankar, Ritwik Sinha, Madalina Fiterau:
Experimentation under Treatment Dependent Network Interference. UAI 2025: 3787-3808 - [c22]Shiv Shankar, Ritwik Sinha, Madalina Fiterau:
Combining A/A Data and LLMs for Improved Content Evaluation. WWW (Companion Volume) 2025: 2749-2753 - [i17]Sidong Zhang, Shiv Shankar, Trang Nguyen, Andrea Fanelli, Madalina Fiterau:
Audio-Visual Speech Separation via Bottleneck Iterative Network. CoRR abs/2507.07270 (2025) - [i16]Trang Nguyen, Jackson Michaels, Madalina Fiterau, David Jensen:
Challenges in Understanding Modality Conflict in Vision-Language Models. CoRR abs/2509.02805 (2025) - 2024
- [j2]Trang Nguyen, Anthony Campbell, Ankit Kumar, Edwin Amponsah, Madalina Fiterau, Leili Shahriyari:
Optimal fusion of genotype and drug embeddings in predicting cancer drug response. Briefings Bioinform. 25(3) (2024) - [c21]Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau:
A/B testing under Interference with Partial Network Information. AISTATS 2024: 19-27 - [c20]Shiv Shankar, Ritwik Sinha, Madalina Fiterau:
On Online Experimentation without Device Identifiers. ICML 2024 - [c19]Shiv Shankar, Ritwik Sinha, Madalina Fiterau:
Estimating Counterfactual Distributions under Interference. ML4H@NeurIPS 2024: 923-940 - [e2]Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga:
Machine Learning for Healthcare Conference, 16-17 August 2024, Toronto, Canada. Proceedings of Machine Learning Research 252, PMLR 2024 [contents] - [i15]Iman Deznabi, Peeyush Kumar, Madalina Fiterau:
Zero-shot Microclimate Prediction with Deep Learning. CoRR abs/2401.02665 (2024) - [i14]Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau:
A/B testing under Interference with Partial Network Information. CoRR abs/2404.10547 (2024) - [i13]Purity Mugambi, Alexandra Meliou, Madalina Fiterau:
Leveraging Foundation Language Models (FLMs) for Automated Cohort Extraction from Large EHR Databases. CoRR abs/2412.11472 (2024) - 2023
- [c18]Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Madalina Fiterau:
Direct Inference of Effect of Treatment (DIET) for a Cookieless World. AISTATS 2023: 1869-1887 - [c17]Iman Deznabi, Madalina Fiterau:
MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series Prediction. CHIL 2023: 509-525 - [c16]Ke Xiao, Erik G. Learned-Miller, Evangelos Kalogerakis, James Priest, Madalina Fiterau:
Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging. MICCAI (7) 2023: 236-246 - [e1]Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga, Serene Yeung:
Machine Learning for Healthcare Conference, MLHC 2023, 11-12 August 2023, New York, USA. Proceedings of Machine Learning Research 219, PMLR 2023 [contents] - [i12]Iman Deznabi, Madalina Fiterau:
MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series Prediction. CoRR abs/2306.10164 (2023) - [i11]Ke Xiao, Erik G. Learned-Miller, Evangelos Kalogerakis, James Priest, Madalina Fiterau:
Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging. CoRR abs/2310.04871 (2023) - 2022
- [c15]Nicholas Polosky, Bruno C. da Silva, Madalina Fiterau, Jithin Jagannath:
Constrained Offline Policy Optimization. ICML 2022: 17801-17810 - [i10]Shiv Shankar, Laure Thompson, Madalina Fiterau:
Progressive Fusion for Multimodal Integration. CoRR abs/2209.00302 (2022) - 2021
- [j1]Iman Deznabi, Tamanna Motahar, Ali Sarvghad, Madalina Fiterau, Narges Mahyar:
Impact of the COVID-19 Pandemic on the Academic Community Results from a survey conducted at University of Massachusetts Amherst. Digit. Gov. Res. Pract. 2(2): 22:1-22:12 (2021) - [c14]Iman Deznabi, Mohit Iyyer, Madalina Fiterau:
Predicting in-hospital mortality by combining clinical notes with time-series data. ACL/IJCNLP (Findings) 2021: 4026-4031 - [c13]Edmond Cunningham, Madalina Fiterau:
A Change of Variables Method For Rectangular Matrix-Vector Products. AISTATS 2021: 2755-2763 - 2020
- [i9]Edmond Cunningham, Renos Zabounidis, Abhinav Agrawal, Ina Fiterau, Daniel Sheldon:
Normalizing Flows Across Dimensions. CoRR abs/2006.13070 (2020) - [i8]Purva Pruthi, Javier González, Xiaoyu Lu, Madalina Fiterau:
Structure Mapping for Transferability of Causal Models. CoRR abs/2007.09445 (2020)
2010 – 2019
- 2019
- [c12]Debasmita Ghose, Shasvat Mukeshkumar Desai, Sneha Bhattacharya, Deep Chakraborty, Madalina Fiterau, Tauhidur Rahman:
Pedestrian Detection in Thermal Images Using Saliency Maps. CVPR Workshops 2019: 988-997 - [c11]Surya Teja Devarakonda, Yeahuay Joie Wu, Yi Ren Fung, Madalina Fiterau:
FLARe: Forecasting by Learning Anticipated Representations. MLHC 2019: 53-65 - [i7]Debasmita Ghose, Shasvat Mukeshkumar Desai, Sneha Bhattacharya, Deep Chakraborty, Madalina Fiterau, Tauhidur Rahman:
Pedestrian Detection in Thermal Images using Saliency Maps. CoRR abs/1904.06859 (2019) - [i6]Ziqiang Guan, Ritesh Kumar, Yi Ren Fung, Yeahuay Wu, Madalina Fiterau:
A Comprehensive Study of Alzheimer's Disease Classification Using Convolutional Neural Networks. CoRR abs/1904.07950 (2019) - [i5]Yeahuay Joie Wu, Surya Teja Devarakonda, Madalina Fiterau:
FLARe: Forecasting by Learning Anticipated Representations. CoRR abs/1904.08930 (2019) - [i4]Bhanu Pratap Singh, Iman Deznabi, Bharath Narasimhan, Bryon Kucharski, Rheeya Uppaal, Akhila Josyula, Madalina Fiterau:
Multi-resolution Networks For Flexible Irregular Time Series Modeling (Multi-FIT). CoRR abs/1905.00125 (2019) - [i3]Yi Ren Fung, Ziqiang Guan, Ritesh Kumar, Yeahuay Joie Wu, Madalina Fiterau:
Alzheimer's Disease Brain MRI Classification: Challenges and Insights. CoRR abs/1906.04231 (2019) - [i2]Abhinav Shaw, Natcha Simsiri, Iman Deznaby, Madalina Fiterau, Tauhidur Rahman:
Personalized Student Stress Prediction with Deep Multitask Network. CoRR abs/1906.11356 (2019) - 2018
- [i1]Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones, Irene Chen, Corey Chivers, Adrian V. Dalca, Samuel G. Finlayson, Madalina Fiterau, Jason Alan Fries, Marzyeh Ghassemi, Mike Hughes, Bruno Jedynak, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi:
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR abs/1811.07216 (2018) - 2017
- [c10]Madalina Fiterau, Suvrat Bhooshan, Jason A. Fries, Charles Bournhonesque, Jennifer L. Hicks, Eni Halilaj, Christopher Ré, Scott L. Delp:
ShortFuse: Biomedical Time Series Representations in the Presence of Structured Information. MLHC 2017: 59-74 - 2016
- [c9]Peter Kontschieder, Madalina Fiterau, Antonio Criminisi, Samuel Rota Bulò:
Deep Neural Decision Forests. IJCAI 2016: 4190-4194 - [c8]Donghan Wang, Madalina Fiterau, Artur Dubrawski:
VIPR: An Interactive Tool for Meaningful Visualization of High-Dimensional Data. IJCAI 2016: 4274-4275 - 2015
- [b1]Madalina Fiterau:
Discovering Compact and Informative Structures through Data Partitioning. Carnegie Mellon University, USA, 2015 - [c7]Matt Barnes, Nick Gisolfi, Madalina Fiterau, Artur Dubrawski:
Leveraging Common Structure to Improve Prediction across Related Datasets. AAAI 2015: 4144-4145 - [c6]Madalina Fiterau, Artur Dubrawski:
Active Learning for Informative Projection Retrieval. AAAI 2015: 4158-4159 - [c5]Nick Gisolfi, Madalina Fiterau, Artur Dubrawski:
Finding Meaningful Gaps to Guide Data Acquisition for a Radiation Adjudication System. AAAI 2015: 4164-4165 - [c4]Peter Kontschieder, Madalina Fiterau, Antonio Criminisi, Samuel Rota Bulò:
Deep Neural Decision Forests. ICCV 2015: 1467-1475 - 2013
- [c3]Madalina Fiterau, Artur Dubrawski:
Informative Projection Recovery for Classification, Clustering and Regression. ICMLA (1) 2013: 15-20 - 2012
- [c2]Madalina Fiterau, Artur Dubrawski:
Projection Retrieval for Classification. NIPS 2012: 3032-3040
2000 – 2009
- 2009
- [c1]Madalina Fiterau, Olga Ormond, Gabriel-Miro Muntean:
Performance of handover for multiple users in heterogeneous wireless networks. LCN 2009: 257-260
Coauthor Index
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last updated on 2025-10-13 22:09 CEST by the dblp team
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