1 citations · 3 across the 7 of their papers we have counts for
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Q-PACE: Dynamic Precision Allocation for Quantization-Aware Training
Alexandra Volkova, Matin Ansaripour, Erik Schultheis +2
Quantization-aware training (QAT) leverages lower-precision arithmetic to reduce the cost of LLM deployment, but aggressive quantization degrades final model performance. A common…
Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence
Matin Ansaripour, Shayan Talaei, Giorgi Nadiradze +1
Distributed optimization is the standard way of speeding up machine learning training, and most of the research in the area focuses on distributed first-order, gradient-based metho…
Learning Provably Stabilizing Neural Controllers for Discrete-Time Stochastic Systems
Matin Ansaripour, Krishnendu Chatterjee, Thomas A. Henzinger +2
We consider the problem of learning control policies in discrete-time stochastic systems which guarantee that the system stabilizes within some specified stabilization region with…