We study the problem of load balancing the traffic from a set of unicast and multicast sessions. The problem is formulated as an optimization problem. However, we assume that the g...
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
We explore the feasibility of linear interference alignment (IA) in MIMO cellular networks. Each base station (BTS) has Nt transmit antennas, each mobile has Nr receive antennas, ...
We design distributed and quantized average consensus algorithms on arbitrary connected networks. By construction, quantized algorithms cannot produce a real, analog average. Inst...