Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Motivated by a broad range of potential applications, we address the quantile prediction problem of real-valued time series. We present a sequential quantile forecasting model bas...
We introduce and analyze a deterministic fluid model that serves as an approximation for the Gt/GI/st + GI manyserver queueing model, which has a general time-varying arrival pro...
—This paper addresses the independent component analysis (ICA) of quaternion random vectors. In particular, we focus on the Gaussian case and therefore only consider the quaterni...
We study iterative randomized greedy algorithms for generating (elimination) orderings with small induced width and state space size - two parameters known to bound the complexity...
Kalev Kask, Andrew Gelfand, Lars Otten, Rina Decht...