Scalable similarity search is the core of many large scale learning or data mining applications. Recently, many research results demonstrate that one promising approach is creatin...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
We focus on detecting intrusions in ad hoc networks using the misuse detection technique. We allow for detection modules that periodically stop functioning due to operational failu...
In this work we investigate an inverse geometry problem. Given a light source, a diffuse plane and a caustic image, how must a geometric object look like (transmissive or reflect...