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cs.LG2026
When Sparsity Breaks Connectivity: Functional Reachability and Guided Topology Dynamics in Extreme Sparse Training
Mohammad Pasande, Mateusz Jaworski, Jeroen Rook +1
Dynamic Sparse Training (DST) periodically prunes and regrows connections, inducing a discrete dynamical mechanism over network topologies. At extreme sparsity (), this d…
cs.LG2022★ 1 cited
Stochastic First-Order Learning for Large-Scale Flexibly Tied Gaussian Mixture Model
Mohammad Pasande, Reshad Hosseini, Babak Nadjar Araabi
Gaussian Mixture Models (GMMs) are one of the most potent parametric density models used extensively in many applications. Flexibly-tied factorization of the covariance matrices in…