4 citations · 5 across the 10 of their papers we have counts for
10 papers
Diagnosing and Mitigating Compounding Failures in Agentic Persuasion via Taxonomic Strategy Retrieval
Sana Ayromlou, Purvi Sehgal, Pradyumna Narayana
Foundation-model agents in multi-step, open-ended environments frequently suffer from compounding errors, where early mistakes contaminate long-horizon trajectories. While Multi-Ag…
MIDST Challenge at SaTML 2025: Membership Inference over Diffusion-models-based Synthetic Tabular data
Masoumeh Shafieinejad, Xi He, Mahshid Alinoori +6
Synthetic data is often perceived as a silver-bullet solution to data anonymization and privacy-preserving data publishing. Drawn from generative models like diffusion models, synt…
Adaptive Latent-Space Constraints in Personalized Federated Learning
Sana Ayromlou, Fatemeh Tavakoli, D. B. Emerson
Federated learning (FL) is an effective and widely used approach to training deep learning models on decentralized datasets held by distinct clients. FL also strengthens both secur…
Federated Impression for Learning with Distributed Heterogeneous Data
Atrin Arya, Sana Ayromlou, Armin Saadat +2
Standard deep learning-based classification approaches may not always be practical in real-world clinical applications, as they require a centralized collection of all samples. Fed…
CCSI: Continual Class-Specific Impression for Data-free Class Incremental Learning
Sana Ayromlou, Teresa Tsang, Purang Abolmaesumi +1
In real-world clinical settings, traditional deep learning-based classification methods struggle with diagnosing newly introduced disease types because they require samples from al…
Can Generative Models Improve Self-Supervised Representation Learning?
Sana Ayromlou, Vahid Reza Khazaie, Fereshteh Forghani +1
The rapid advancement in self-supervised representation learning has highlighted its potential to leverage unlabeled data for learning rich visual representations. However, the exi…
A Comprehensive View of Personalized Federated Learning on Heterogeneous Clinical Datasets
Fatemeh Tavakoli, D. B. Emerson, Sana Ayromlou +5
Federated learning (FL) is increasingly being recognized as a key approach to overcoming the data silos that so frequently obstruct the training and deployment of machine-learning…
Class Impression for Data-free Incremental Learning
Sana Ayromlou, Purang Abolmaesumi, Teresa Tsang +1
Standard deep learning-based classification approaches require collecting all samples from all classes in advance and are trained offline. This paradigm may not be practical in rea…
SVG-Net: An SVG-based Trajectory Prediction Model
Mohammadhossein Bahari, Vahid Zehtab, Sadegh Khorasani +3
Anticipating motions of vehicles in a scene is an essential problem for safe autonomous driving systems. To this end, the comprehension of the scene's infrastructure is often the m…
Dementia Severity Classification under Small Sample Size and Weak Supervision in Thick Slice MRI
Reza Shirkavand, Sana Ayromlou, Soroush Farghadani +7
Early detection of dementia through specific biomarkers in MR images plays a critical role in developing support strategies proactively. Fazekas scale facilitates an accurate quant…