We study finite-sum distributed optimization problems with n-clients und...
In this short note, we give the convergence analysis of the policy in th...
In this paper, we follow Eftekhari's work to give a non-local convergenc...
In this paper, we propose the greedy and random Broyden's method for sol...
We consider the fundamental problem of learning linear predictors (i.e.,...
We propose Meta-Regularization, a novel approach for the adaptive
choice...
Network pruning, or sparse network has a long history and practical
sign...
Quantized Neural Networks (QNNs) use low bit-width fixed-point numbers f...
Numerous empirical evidence has corroborated that the noise plays a cruc...
Stochastic variance-reduced gradient (SVRG) is a classical optimization
...