Shale: an efficient algorithm for allocation of guaranteed display advertising
V Bharadwaj, P Chen, W Ma, C Nagarajan… - Proceedings of the 18th …, 2012 - dl.acm.org
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012•dl.acm.org
Motivated by the problem of optimizing allocation in guaranteed display advertising, we
develop an efficient, lightweight method of generating a compact allocation plan that can be
used to guide ad server decisions. The plan itself uses just O (1) state per guaranteed
contract, is robust to noise, and allows us to serve (provably) nearly optimally. The
optimization method we develop is scalable, with a small in-memory footprint, and working
in linear time per iteration. It is also" stop-anytime", meaning that time-critical applications …
develop an efficient, lightweight method of generating a compact allocation plan that can be
used to guide ad server decisions. The plan itself uses just O (1) state per guaranteed
contract, is robust to noise, and allows us to serve (provably) nearly optimally. The
optimization method we develop is scalable, with a small in-memory footprint, and working
in linear time per iteration. It is also" stop-anytime", meaning that time-critical applications …
Motivated by the problem of optimizing allocation in guaranteed display advertising, we develop an efficient, lightweight method of generating a compact allocation plan that can be used to guide ad server decisions. The plan itself uses just O(1) state per guaranteed contract, is robust to noise, and allows us to serve (provably) nearly optimally.
The optimization method we develop is scalable, with a small in-memory footprint, and working in linear time per iteration. It is also "stop-anytime", meaning that time-critical applications can stop early and still get a good serving solution. Thus, it is particularly useful for optimizing the large problems arising in the context of display advertising. We demonstrate the effectiveness of our algorithm using actual Yahoo! data.