Convex Co-embedding. - Farzaneh Mirzazadeh; Yuhong Guo; Dale Schuurmans (AAAI, 2014)

Embedding Inference for Structured Multilabel Prediction. - Farzaneh Mirzazadeh; Siamak Ravanbakhsh; Nan Ding 002; Dale Schuurmans (NIPS, 2015)

Scalable Metric Learning for Co-Embedding. - Farzaneh Mirzazadeh; Martha White; András György 001; Dale Schuurmans (ECML/PKDD (1), 2015)

Learning Embeddings into Entropic Wasserstein Spaces. - Charlie Frogner; Farzaneh Mirzazadeh; Justin Solomon 001 (ICLR (Poster), 2019)

Alleviating Label Switching with Optimal Transport. - Pierre Monteiller; Sebastian Claici; Edward Chien; Farzaneh Mirzazadeh; Justin M. Solomon; Mikhail Yurochkin (NeurIPS, 2019)

Hierarchical Optimal Transport for Document Representation. - Mikhail Yurochkin; Sebastian Claici; Edward Chien; Farzaneh Mirzazadeh; Justin M. Solomon (NeurIPS, 2019)

BreGMN: scaled-Bregman Generative Modeling Networks. - Akash Srivastava; Kristjan H. Greenewald; Farzaneh Mirzazadeh (CoRR, 2019)

GC-Flow: A Graph-Based Flow Network for Effective Clustering. - Tianchun Wang; Farzaneh Mirzazadeh; Xiang Zhang 001; Jie Chen (ICML, 2023)

From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifesto. - Segev Wasserkrug; Léonard Boussioux; Dick den Hertog; Farzaneh Mirzazadeh; S. Ilker Birbil; Jannis Kurtz; Donato Maragno (CoRR, 2024)

Enhancing Decision Making Through the Integration of Large Language Models and Operations Research Optimization. - Segev Wasserkrug; Léonard Boussioux; Dick den Hertog; Farzaneh Mirzazadeh; S. Ilker Birbil; Jannis Kurtz; Donato Maragno (AAAI, 2025)