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ORCIDAnna Choromanska
Person information
- affiliation: New York University, Courant Institute of Mathematical Sciences
- affiliation: Columbia University New York, Department of Electrical Engineering
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Books and Theses
- 2014
[b1]Anna Choromanska:
Selected machine learning reductions. Columbia University, USA, 2014
Journal Articles
- 2023
- [j8]Tolga Dimlioglu, Jing Wang
, Devansh Bisla, Anna Choromanska, Simon Odie, Leon Bukhman, Afolabi Olomola, James D. Wong:
Automatic document classification via transformers for regulations compliance management in large utility companies. Neural Comput. Appl. 35(23): 17167-17185 (2023) - 2022
- [j7]Apoorva Nandini Saridena, Anna Choromanska:
DNN Patching: Progressive Fixing and Augmenting the Functionalities of DNNs for Autonomous Vehicles. IEEE Robotics Autom. Lett. 7(2): 3257-3264 (2022) - 2020
- [j6]Naman Patel, Apoorva Nandini Saridena, Anna Choromanska, Prashanth Krishnamurthy, Farshad Khorrami:
Learning-Based Real-Time Process-Aware Anomaly Monitoring for Assured Autonomy. IEEE Trans. Intell. Veh. 5(4): 659-669 (2020) - 2019
- [j5]Anna Choromanska, Ish Kumar Jain:
Extreme Multiclass Classification Criteria. Comput. 7(1): 16 (2019) - [j4]Yunfei Teng, Anna Choromanska:
Invertible Autoencoder for Domain Adaptation. Comput. 7(2): 20 (2019) - [j3]Benjamin Cowen, Apoorva Nandini Saridena, Anna Choromanska:
LSALSA: accelerated source separation via learned sparse coding. Mach. Learn. 108(8-9): 1307-1327 (2019) - [j2]Naman Patel, Anna Choromanska, Prashanth Krishnamurthy, Farshad Khorrami:
A deep learning gated architecture for UGV navigation robust to sensor failures. Robotics Auton. Syst. 116: 80-97 (2019) - 2016
- [j1]Anna Choromanska, Krzysztof Choromanski, Geetha Jagannathan, Claire Monteleoni:
Differentially-private learning of low dimensional manifolds. Theor. Comput. Sci. 620: 91-104 (2016)
Conference and Workshop Papers
- 2024
- [c33]Tolga Dimlioglu, Anna Choromanska:
GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models. AISTATS 2024: 2251-2259 - 2023
- [c32]Shihong Fang, Haoran Zhu, Devansh Bisla, Anna Choromanska, Satish Ravindran, Dongyin Ren, Ryan Wu:
ERASE-Net: Efficient Segmentation Networks for Automotive Radar Signals. ICRA 2023: 9331-9337 - 2022
- [c31]Shihong Fang, Anna Choromanska:
Backdoor Attacks on the DNN Interpretation System. AAAI 2022: 561-570 - [c30]Devansh Bisla, Jing Wang, Anna Choromanska:
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape. AISTATS 2022: 8299-8339 - [c29]Yunfei Teng, Anna Choromanska, Murray Campbell, Songtao Lu, Parikshit Ram, Lior Horesh:
Overcoming Catastrophic Forgetting via Direction-Constrained Optimization. ECML/PKDD (1) 2022: 675-692 - 2021
- [c28]Devansh Bisla, Apoorva Nandini Saridena, Anna Choromanska:
A Theoretical-Empirical Approach to Estimating Sample Complexity of DNNs. CVPR Workshops 2021: 3270-3280 - 2020
- [c27]Maryam Majzoubi, Anna Choromanska:
LdSM: Logarithm-depth Streaming Multi-label Decision Trees. AISTATS 2020: 4247-4257 - [c26]Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael I. Jordan:
Learning to Score Behaviors for Guided Policy Optimization. ICML 2020: 7445-7454 - [c25]Shihong Fang, Anna Choromanska:
Multi-modal Experts Network for Autonomous Driving. ICRA 2020: 6439-6445 - 2019
- [c24]Devansh Bisla, Anna Choromanska, Russell S. Berman, Jennifer A. Stein, David Polsky:
Towards Automated Melanoma Detection With Deep Learning: Data Purification and Augmentation. CVPR Workshops 2019: 2720-2728 - [c23]Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel, Ronny Luss, Mattia Rigotti, Irina Rish, Paolo Diachille, Viatcheslav Gurev, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf:
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables. ICML 2019: 1193-1202 - [c22]Shihong Fang, Anna Choromanska:
Reconfigurable Network for Efficient Inferencing in Autonomous Vehicles. ICRA 2019: 1183-1189 - [c21]Yunfei Teng, Wenbo Gao, François Chalus, Anna Choromanska, Donald Goldfarb, Adrian Weller:
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models. NeurIPS 2019: 9821-9831 - 2018
- [c20]Shervin Minaee, Yao Wang, Anna Choromanska, Sohae Chung, Xiuyuan Wang, Els Fieremans, Steven Flanagan, Joseph Rath, Yvonne W. Lui:
A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRI. EMBC 2018: 1267-1270 - [c19]Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Larry J. Ackel, Urs Muller, Philip Yeres, Karol Zieba:
VisualBackProp: Efficient Visualization of CNNs for Autonomous Driving. ICRA 2018: 1-8 - [c18]Naman Patel, Apoorva Nandini Saridena, Anna Choromanska, Prashanth Krishnamurthy, Farshad Khorrami:
Adversarial Learning-Based On-Line Anomaly Monitoring for Assured Autonomy. IROS 2018: 6149-6154 - 2017
- [c17]Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif:
Structured adaptive and random spinners for fast machine learning computations. AISTATS 2017: 1020-1029 - [c16]Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Levent Sagun, Riccardo Zecchina:
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys. ICLR (Poster) 2017 - [c15]Yacine Jernite, Anna Choromanska, David A. Sontag:
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation. ICML 2017: 1665-1674 - [c14]Naman Patel, Anna Choromanska, Prashanth Krishnamurthy, Farshad Khorrami:
Sensor modality fusion with CNNs for UGV autonomous driving in indoor environments. IROS 2017: 1531-1536 - 2016
- [c13]Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun:
Binary embeddings with structured hashed projections. ICML 2016: 344-353 - 2015
- [c12]Julita Kulbacka, Marek Kulbacki, Jakub Segen, Anna Choromanska, Jolanta Saczko, Magda Dubinska-Magiera, Malgorzata Kotulska:
Automated Analysis of Images from Confocal Laser Scanning Microscopy Applied to Observation of Calcium Channel Subunits in Nerve Cell Model Line Subjected Electroporation and Calcium. ACIIDS (2) 2015: 297-306 - [c11]Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun:
The Loss Surfaces of Multilayer Networks. AISTATS 2015 - [c10]Anna Choromanska, Yann LeCun, Gérard Ben Arous:
Open Problem: The landscape of the loss surfaces of multilayer networks. COLT 2015: 1756-1760 - [c9]Anna Choromanska, John Langford:
Logarithmic Time Online Multiclass prediction. NIPS 2015: 55-63 - [c8]Sixin Zhang, Anna Choromanska, Yann LeCun:
Deep learning with Elastic Averaging SGD. NIPS 2015: 685-693 - [c7]Sixin Zhang, Anna Choromanska, Yann LeCun:
Deep learning with Elastic Averaging SGD. ICLR (Workshop) 2015 - 2014
- [c6]Aleksandr Y. Aravkin, Anna Choromanska, Dimitri Kanevsky, Tony Jebara:
Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems. ICLR (Workshop Poster) 2014 - 2013
- [c5]Anna Choromanska, Krzysztof Choromanski, Geetha Jagannathan, Claire Monteleoni:
Differentially-Private Learning of Low Dimensional Manifolds. ALT 2013: 249-263 - [c4]Anna Choromanska, Tony Jebara, Hyungtae Kim, Mahesh Mohan, Claire Monteleoni:
Fast Spectral Clustering via the Nyström Method. ALT 2013: 367-381 - 2012
- [c3]Tony Jebara, Anna Choromanska:
Majorization for CRFs and Latent Likelihoods. NIPS 2012: 566-574 - [c2]Anna Choromanska, Claire Monteleoni:
Online Clustering with Experts. ICML On-line Trading of Exploration and Exploitation 2012: 1-18 - [c1]Anna Choromanska, Claire Monteleoni:
Online Clustering with Experts. AISTATS 2012: 227-235
Informal and Other Publications
- 2024
- [i33]Tolga Dimlioglu, Anna Choromanska:
GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models. CoRR abs/2403.04206 (2024) - 2022
- [i32]Devansh Bisla, Jing Wang, Anna Choromanska:
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape. CoRR abs/2201.08025 (2022) - [i31]Shihong Fang, Haoran Zhu, Devansh Bisla, Anna Choromanska, Satish Ravindran, Dongyin Ren, Ryan Wu:
ERASE-Net: Efficient Segmentation Networks for Automotive Radar Signals. CoRR abs/2209.12940 (2022) - [i30]Haoran Zhu, Maryam Majzoubi, Arihant Jain, Anna Choromanska:
TAME: Task Agnostic Continual Learning using Multiple Experts. CoRR abs/2210.03869 (2022) - 2021
- [i29]Devansh Bisla, Apoorva Nandini Saridena, Anna Choromanska:
A Theoretical-Empirical Approach to Estimating Sample Complexity of DNNs. CoRR abs/2105.01867 (2021) - [i28]Yunfei Teng, Jing Wang, Anna Choromanska:
AutoDrop: Training Deep Learning Models with Automatic Learning Rate Drop. CoRR abs/2111.15317 (2021) - [i27]Bernard McShea, Kevin Wright, Denley Lam, Steve Schmidt, Anna Choromanska, Devansh Bisla, Shihong Fang, Alireza Sarmadi, Prashanth Krishnamurthy, Farshad Khorrami:
ESAFE: Enterprise Security and Forensics at Scale. CoRR abs/2112.04114 (2021) - 2020
- [i26]Shihong Fang, Anna Choromanska:
Multi-modal Experts Network for Autonomous Driving. CoRR abs/2009.08876 (2020) - [i25]Jing Wang, Anna Choromanska:
SGB: Stochastic Gradient Bound Method for Optimizing Partition Functions. CoRR abs/2011.01474 (2020) - [i24]Shihong Fang, Anna Choromanska:
Backdoor Attacks on the DNN Interpretation System. CoRR abs/2011.10698 (2020) - [i23]Yunfei Teng, Anna Choromanska, Murray Campbell:
Continual learning with direction-constrained optimization. CoRR abs/2011.12581 (2020) - 2019
- [i22]Devansh Bisla, Anna Choromanska, Jennifer A. Stein, David Polsky, Russell S. Berman:
Skin Lesion Segmentation and Classification with Deep Learning System. CoRR abs/1902.06061 (2019) - [i21]Yunfei Teng, Wenbo Gao, François Chalus, Anna Choromanska, Donald Goldfarb, Adrian Weller:
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models. CoRR abs/1905.10395 (2019) - [i20]Maryam Majzoubi, Anna Choromanska:
LdSM: Logarithm-depth Streaming Multi-label Decision Trees. CoRR abs/1905.10428 (2019) - [i19]Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Anna Choromanska, Krzysztof Choromanski, Michael I. Jordan:
Wasserstein Reinforcement Learning. CoRR abs/1906.04349 (2019) - 2018
- [i18]Shervin Minaee, Yao Wang, Anna Choromanska, Sohae Chung, Xiuyuan Wang, Els Fieremans, Steven Flanagan, Joseph Rath, Yvonne W. Lui:
A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRI. CoRR abs/1802.02925 (2018) - [i17]Yunfei Teng, Anna Choromanska, Mariusz Bojarski:
Invertible Autoencoder for domain adaptation. CoRR abs/1802.06869 (2018) - [i16]Benjamin Cowen, Apoorva Nandini Saridena, Anna Choromanska:
LSALSA: efficient sparse coding in single and multiple dictionary settings. CoRR abs/1802.06875 (2018) - [i15]Devansh Bisla, Anna Choromanska:
VisualBackProp for learning using privileged information with CNNs. CoRR abs/1805.09474 (2018) - [i14]Anna Choromanska, Sadhana Kumaravel, Ronny Luss, Irina Rish, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf:
Beyond Backprop: Alternating Minimization with co-Activation Memory. CoRR abs/1806.09077 (2018) - [i13]Naman Patel, Apoorva Nandini Saridena, Anna Choromanska, Prashanth Krishnamurthy, Farshad Khorrami:
Adversarial Learning-Based On-Line Anomaly Monitoring for Assured Autonomy. CoRR abs/1811.04539 (2018) - 2017
- [i12]Mariusz Bojarski, Philip Yeres, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Lawrence D. Jackel, Urs Muller:
Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car. CoRR abs/1704.07911 (2017) - 2016
- [i11]Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski:
On the boosting ability of top-down decision tree learning algorithm for multiclass classification. CoRR abs/1605.05223 (2016) - [i10]Yacine Jernite, Anna Choromanska, David A. Sontag, Yann LeCun:
Simultaneous Learning of Trees and Representations for Extreme Classification, with Application to Language Modeling. CoRR abs/1610.04658 (2016) - [i9]Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif:
Structured adaptive and random spinners for fast machine learning computations. CoRR abs/1610.06209 (2016) - [i8]Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Levent Sagun, Riccardo Zecchina:
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys. CoRR abs/1611.01838 (2016) - [i7]Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Larry D. Jackel, Urs Muller, Karol Zieba:
VisualBackProp: visualizing CNNs for autonomous driving. CoRR abs/1611.05418 (2016) - 2015
- [i6]Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun:
Binary embeddings with structured hashed projections. CoRR abs/1511.05212 (2015) - 2014
- [i5]Anna Choromanska, John Langford:
Logarithmic Time Online Multiclass prediction. CoRR abs/1406.1822 (2014) - [i4]Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Yann LeCun:
Differentially- and non-differentially-private random decision trees. CoRR abs/1410.6973 (2014) - [i3]Apoorv Agarwal, Anna Choromanska, Krzysztof Choromanski:
Notes on using Determinantal Point Processes for Clustering with Applications to Text Clustering. CoRR abs/1410.6975 (2014) - [i2]Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun:
The Loss Surface of Multilayer Networks. CoRR abs/1412.0233 (2014) - 2013
- [i1]Anna Choromanska, Tony Jebara:
Stochastic Bound Majorization. CoRR abs/1309.5605 (2013)
Coauthor Index
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