A key problem in widely distributed camera networks is geolocating the cameras. This paper considers three scenarios for camera localization: localizing a camera in an unknown env...
Nathan Jacobs, Scott Satkin, Nathaniel Roman, Robe...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Realizing scalable cache coherence in the many-core era comes with a whole new set of constraints and opportunities. It is widely believed that multi-hop, unordered on-chip networ...
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
We introduce virtually-pipelined memory, an architectural technique that efficiently supports high-bandwidth, uniform latency memory accesses, and high-confidence throughput eve...