Majorization for CRFs and Latent Likelihoods. - Tony Jebara; Anna Choromanska (NIPS, 2012)

Online Clustering with Experts. - Anna Choromanska; Claire Monteleoni (ICML On-line Trading of Exploration and Exploitation, 2012)

Fast Spectral Clustering via the Nyström Method. - Anna Choromanska; Tony Jebara; Hyungtae Kim; Mahesh Mohan; Claire Monteleoni (ALT, 2013)

Stochastic Bound Majorization. - Anna Choromanska; Tony Jebara (CoRR, 2013)

Notes on using Determinantal Point Processes for Clustering with Applications to Text Clustering. - Apoorv Agarwal; Anna Choromanska; Krzysztof Choromanski (CoRR, 2014)

Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems. - Aleksandr Y. Aravkin; Anna Choromanska; Dimitri Kanevsky; Tony Jebara (ICLR (Workshop Poster), 2014)

Differentially- and non-differentially-private random decision trees. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Yann LeCun (CoRR, 2014)

The Loss Surface of Multilayer Networks. - Anna Choromanska; Mikael Henaff; Michaël Mathieu; Gérard Ben Arous; Yann LeCun (CoRR, 2014)

Selected machine learning reductions. - Anna Choromanska (2014)

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. - Julita Kulbacka; Marek Kulbacki; Jakub Segen; Anna Choromanska; Jolanta Saczko; Magda Dubinska-Magiera; Malgorzata Kotulska (ACIIDS (2), 2015)

The Loss Surfaces of Multilayer Networks. - Anna Choromanska; Mikael Henaff; Michaël Mathieu; Gérard Ben Arous; Yann LeCun (AISTATS, 2015)

Open Problem: The landscape of the loss surfaces of multilayer networks. - Anna Choromanska; Yann LeCun; Gérard Ben Arous (COLT, 2015)

Logarithmic Time Online Multiclass prediction. - Anna Choromanska; John Langford 001 (NIPS, 2015)

Deep learning with Elastic Averaging SGD. - Sixin Zhang; Anna Choromanska; Yann LeCun (ICLR (Workshop), 2015)

Binary embeddings with structured hashed projections. - Anna Choromanska; Krzysztof Choromanski; Mariusz Bojarski; Tony Jebara; Sanjiv Kumar; Yann LeCun (ICML, 2016)

VisualBackProp: visualizing CNNs for autonomous driving. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Bernhard Firner; Larry D. Jackel; Urs Muller; Karol Zieba (CoRR, 2016)

On the boosting ability of top-down decision tree learning algorithm for multiclass classification. - Anna Choromanska; Krzysztof Choromanski; Mariusz Bojarski (CoRR, 2016)

Simultaneous Learning of Trees and Representations for Extreme Classification, with Application to Language Modeling. - Yacine Jernite; Anna Choromanska; David A. Sontag; Yann LeCun (CoRR, 2016)

Differentially-private learning of low dimensional manifolds. - Anna Choromanska; Krzysztof Choromanski; Geetha Jagannathan; Claire Monteleoni (Theor. Comput. Sci., 2016)

Structured adaptive and random spinners for fast machine learning computations. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Francois Fagan; Cédric Gouy-Pailler; Anne Morvan; Nourhan Sakr; Tamás Sarlós; Jamal Atif (AISTATS, 2017)

Entropy-SGD: Biasing Gradient Descent Into Wide Valleys. - Pratik Chaudhari; Anna Choromanska; Stefano Soatto; Yann LeCun; Carlo Baldassi; Christian Borgs; Jennifer T. Chayes; Levent Sagun; Riccardo Zecchina (ICLR (Poster), 2017)

Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation. - Yacine Jernite; Anna Choromanska; David A. Sontag (ICML, 2017)

Sensor modality fusion with CNNs for UGV autonomous driving in indoor environments. - Naman Patel; Anna Choromanska; Prashanth Krishnamurthy; Farshad Khorrami (IROS, 2017)

Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car. - Mariusz Bojarski; Philip Yeres; Anna Choromanska; Krzysztof Choromanski; Bernhard Firner; Lawrence D. Jackel; Urs Muller (CoRR, 2017)

A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRI. - Shervin Minaee; Yao Wang 001; Anna Choromanska; Sohae Chung; Xiuyuan Wang 001; Els Fieremans; Steven Flanagan 001; Joseph Rath; Yvonne W. Lui (EMBC, 2018)

VisualBackProp: Efficient Visualization of CNNs for Autonomous Driving. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Bernhard Firner; Larry J. Ackel; Urs Muller; Philip Yeres; Karol Zieba (ICRA, 2018)

Adversarial Learning-Based On-Line Anomaly Monitoring for Assured Autonomy. - Naman Patel; Apoorva Nandini Saridena; Anna Choromanska; Prashanth Krishnamurthy; Farshad Khorrami (IROS, 2018)

Invertible Autoencoder for domain adaptation. - Yunfei Teng; Anna Choromanska; Mariusz Bojarski (CoRR, 2018)

LSALSA: efficient sparse coding in single and multiple dictionary settings. - Benjamin Cowen; Apoorva Nandini Saridena; Anna Choromanska (CoRR, 2018)

VisualBackProp for learning using privileged information with CNNs. - Devansh Bisla; Anna Choromanska (CoRR, 2018)

Beyond Backprop: Alternating Minimization with co-Activation Memory. - Anna Choromanska; Sadhana Kumaravel; Ronny Luss; Irina Rish; Brian Kingsbury; Ravi Tejwani; Djallel Bouneffouf 001 (CoRR, 2018)

Towards Automated Melanoma Detection With Deep Learning: Data Purification and Augmentation. - Devansh Bisla; Anna Choromanska; Russell S. Berman; Jennifer A. Stein; David Polsky (CVPR Workshops, 2019)

Beyond Backprop: Online Alternating Minimization with Auxiliary Variables. - Anna Choromanska; Benjamin Cowen; Sadhana Kumaravel; Ronny Luss; Mattia Rigotti; Irina Rish; Paolo Diachille; Viatcheslav Gurev; Brian Kingsbury; Ravi Tejwani; Djallel Bouneffouf 001 (ICML, 2019)

Reconfigurable Network for Efficient Inferencing in Autonomous Vehicles. - Shihong Fang; Anna Choromanska (ICRA, 2019)

Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models. - Yunfei Teng; Wenbo Gao; François Chalus; Anna Choromanska; Donald Goldfarb; Adrian Weller (NeurIPS, 2019)

Extreme Multiclass Classification Criteria. - Anna Choromanska; Ish Kumar Jain (Comput., 2019)

Invertible Autoencoder for Domain Adaptation. - Yunfei Teng; Anna Choromanska (Comput., 2019)

Skin Lesion Segmentation and Classification with Deep Learning System. - Devansh Bisla; Anna Choromanska; Jennifer A. Stein; David Polsky; Russell S. Berman (CoRR, 2019)

Wasserstein Reinforcement Learning. - Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang; Anna Choromanska; Krzysztof Choromanski; Michael I. Jordan (CoRR, 2019)

LSALSA: accelerated source separation via learned sparse coding. - Benjamin Cowen; Apoorva Nandini Saridena; Anna Choromanska (Mach. Learn., 2019)

A deep learning gated architecture for UGV navigation robust to sensor failures. - Naman Patel; Anna Choromanska; Prashanth Krishnamurthy; Farshad Khorrami (Robotics Auton. Syst., 2019)

LdSM: Logarithm-depth Streaming Multi-label Decision Trees. - Maryam Majzoubi; Anna Choromanska (AISTATS, 2020)

Learning to Score Behaviors for Guided Policy Optimization. - Aldo Pacchiano; Jack Parker-Holder; Yunhao Tang; Krzysztof Choromanski; Anna Choromanska; Michael I. Jordan (ICML, 2020)

Multi-modal Experts Network for Autonomous Driving. - Shihong Fang; Anna Choromanska (ICRA, 2020)

SGB: Stochastic Gradient Bound Method for Optimizing Partition Functions. - Jing Wang 178; Anna Choromanska (CoRR, 2020)

Continual learning with direction-constrained optimization. - Yunfei Teng; Anna Choromanska; Murray Campbell (CoRR, 2020)

Learning-Based Real-Time Process-Aware Anomaly Monitoring for Assured Autonomy. - Naman Patel; Apoorva Nandini Saridena; Anna Choromanska; Prashanth Krishnamurthy; Farshad Khorrami (IEEE Trans. Intell. Veh., 2020)

A Theoretical-Empirical Approach to Estimating Sample Complexity of DNNs. - Devansh Bisla; Apoorva Nandini Saridena; Anna Choromanska (CVPR Workshops, 2021)

ESAFE: Enterprise Security and Forensics at Scale. - Bernard McShea; Kevin Wright; Denley Lam; Steve Schmidt; Anna Choromanska; Devansh Bisla; Shihong Fang; Alireza Sarmadi; Prashanth Krishnamurthy; Farshad Khorrami (CoRR, 2021)

Backdoor Attacks on the DNN Interpretation System. - Shihong Fang; Anna Choromanska (AAAI, 2022)

Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape. - Devansh Bisla; Jing Wang 178; Anna Choromanska (AISTATS, 2022)

Overcoming Catastrophic Forgetting via Direction-Constrained Optimization. - Yunfei Teng; Anna Choromanska; Murray Campbell; Songtao Lu; Parikshit Ram; Lior Horesh (ECML/PKDD (1), 2022)

DNN Patching: Progressive Fixing and Augmenting the Functionalities of DNNs for Autonomous Vehicles. - Apoorva Nandini Saridena; Anna Choromanska (IEEE Robotics Autom. Lett., 2022)

ERASE-Net: Efficient Segmentation Networks for Automotive Radar Signals. - Shihong Fang; Haoran Zhu; Devansh Bisla; Anna Choromanska; Satish Ravindran; Dongyin Ren; Ryan Wu (ICRA, 2023)

Automatic document classification via transformers for regulations compliance management in large utility companies. - Tolga Dimlioglu; Jing Wang 178; Devansh Bisla; Anna Choromanska; Simon Odie; Leon Bukhman; Afolabi Olomola; James D. Wong (Neural Comput. Appl., 2023)

GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models. - Tolga Dimlioglu; Anna Choromanska (AISTATS, 2024)

Wake-Sleep Energy Based Models for Continual Learning. - Vaibhav Singh; Anna Choromanska; Shuang Li 013; Yilun Du (CVPR Workshops, 2024)

TAME: Task Agnostic Continual Learning using Multiple Experts. - Haoran Zhu; Maryam Majzoubi; Arihant Jain; Anna Choromanska (CVPR Workshops, 2024)

Adjacent Leader Decentralized Stochastic Gradient Descent. - Haoze He; Jing Wang 178; Anna Choromanska (ECAI, 2024)

Multi-View Radar Autoencoder for Self-Supervised Automotive Radar Representation Learning. - Haoran Zhu; Haoze He; Anna Choromanska; Satish Ravindran; Binbin Shi; Lihui Chen (IV, 2024)

AutoDrop: Training Deep Learning Models with Automatic Learning Rate Drop. - Jing Wang 178; Yunfei Teng; Anna Choromanska (UAI, 2024)

Task-Level Contrastiveness for Cross-Domain Few-Shot Learning. - Kristi Topollai; Anna Choromanska (CVPR Workshops, 2025)

AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR Data. - Haoran Zhu; Zhenyuan Dong; Kristi Topollai; Anna Choromanska (CoRR, 2025)

A Survey of Optimization Methods for Training DL Models: Theoretical Perspective on Convergence and Generalization. - Jing Wang 178; Anna Choromanska (CoRR, 2025)

Communication-Efficient Distributed Training for Collaborative Flat Optima Recovery in Deep Learning. - Tolga Dimlioglu; Anna Choromanska (CoRR, 2025)