170 citations · 341 across the 11 of their papers we have counts for
17 papers
A4-MR: Abnormality-aware Anatomical Alignment for MR
Noel D'souza, Zhijian Yang, Nishank Singla +14
Recent advances in large-scale foundation models have enabled strong generalization across a wide range of clinical and research tasks in magnetic resonance imaging (MRI). However,…
Decipher-MR: A Vision-Language Foundation Model for 3D MRI Representations
Zhijian Yang, Noel DSouza, Istvan Megyeri +11
Magnetic Resonance Imaging is a critical imaging modality in clinical diagnosis and research, yet its complexity and heterogeneity hinder scalable, generalizable machine learning.…
Multi Anatomy X-Ray Foundation Model
Nishank Singla, Krisztian Koos, Farzin Haddadpour +5
X-ray imaging is a ubiquitous in radiology, yet most existing AI foundation models are limited to chest anatomy and fail to generalize across broader clinical tasks. In this work,…
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
Konstantinos E. Nikolakakis, Farzin Haddadpour, Amin Karbasi +1
We provide sharp path-dependent generalization and excess risk guarantees for the full-batch Gradient Descent (GD) algorithm on smooth losses (possibly non-Lipschitz, possibly nonc…
Learning Distributionally Robust Models at Scale via Composite Optimization
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi +1
To train machine learning models that are robust to distribution shifts in the data, distributionally robust optimization (DRO) has been proven very effective. However, the existin…
Black-Box Generalization: Stability of Zeroth-Order Learning
Konstantinos E. Nikolakakis, Farzin Haddadpour, Dionysios S. Kalogerias +1
We provide the first generalization error analysis for black-box learning through derivative-free optimization. Under the assumption of a Lipschitz and smooth unknown loss, we cons…
FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching
Farzin Haddadpour, Belhal Karimi, Ping Li +1
Communication complexity and privacy are the two key challenges in Federated Learning where the goal is to perform a distributed learning through a large volume of devices. In this…
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari +1
In federated learning, communication cost is often a critical bottleneck to scale up distributed optimization algorithms to collaboratively learn a model from millions of devices w…
Efficient Fair Principal Component Analysis
Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati +1
It has been shown that dimension reduction methods such as PCA may be inherently prone to unfairness and treat data from different sensitive groups such as race, color, sex, etc.,…
On the Convergence of Local Descent Methods in Federated Learning
Farzin Haddadpour, Mehrdad Mahdavi
In federated distributed learning, the goal is to optimize a global training objective defined over distributed devices, where the data shard at each device is sampled from a possi…
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi +1
Communication overhead is one of the key challenges that hinders the scalability of distributed optimization algorithms. In this paper, we study local distributed SGD, where data i…
Straggler-Resilient and Communication-Efficient Distributed Iterative Linear Solver
Farzin Haddadpour, Yaoqing Yang, Malhar Chaudhari +2
We propose a novel distributed iterative linear inverse solver method. Our method, PolyLin, has significantly lower communication cost, both in terms of number of rounds as well as…
On the Optimal Recovery Threshold of Coded Matrix Multiplication
Sanghamitra Dutta, Mohammad Fahim, Farzin Haddadpour +3
We provide novel coded computation strategies for distributed matrix-matrix products that outperform the recent "Polynomial code" constructions in recovery threshold, i.e., the req…
Low-Complexity Stochastic Generalized Belief Propagation
Farzin Haddadpour, Mahdi Jafari Siavoshani, Morteza Noshad
The generalized belief propagation (GBP), introduced by Yedidia et al., is an extension of the belief propagation (BP) algorithm, which is widely used in different problems involve…
Simulation of a Channel with Another Channel
Farzin Haddadpour, Mohammad Hossein Yassaee, Salman Beigi +2
In this paper, we study the problem of simulating a DMC channel from another DMC channel under an average-case and an exact model. We present several achievability and infeasibilit…
On AVCs with Quadratic Constraints
Farzin Haddadpour, Mahdi Jafari Siavoshani, Mayank Bakshi +1
In this work we study an Arbitrarily Varying Channel (AVC) with quadratic power constraints on the transmitter and a so-called "oblivious" jammer (along with additional AWGN) under…
Coordination via a relay
Farzin Haddadpour, Mohammad Hossein Yassaee, Amin Gohari +1
In this paper, we study the problem of coordinating two nodes which can only exchange information via a relay at limited rates. The nodes are allowed to do a two-round interactive…