Publications

Wireless Gigabit networks based on the 5G New Radio and WiGig standards are expected to enable new throughput-intensive applications such as Virtual/Augmented Reality, high-resolution video chats,

LTE's uplink (UL) efficiency critically depends on how the interference across different cells is controlled.

Learning algorithms have been used both on feed-forward deterministic networks and on feed-back statistical networks to capture input-output relations and do pattern classification.

This talk covers some fundamental primitives in text interpretation -- named entity disambiguation, topic labeling and extending knowledge bases -- and describes learning solutions for these primit

We study regenerative stopping problems which involve computing decision making strategies to optimize long-term average cost.

The problem of inductive inference refers to extracting general rules, learning concepts from a training set consisting of some fraction of the total number of possible examples of the concept.

Layered neural networks are of interest as a tool to implement input-output mappings.

Layered neural networks are of interest as a tool to implement input-output mappings.

The problem of inductive inference refers to extracting general rules, learning concepts from a training set consisting of some fraction of the total number of possible examples of the concept.

Layered neural networks are of interest as a tool to implement input-output mappings.