Publications by Victor Bittorf

@inproceedings{abc,
	author = {Victor Bittorf and Marcel Kornacker and Christopher R{\'e} and Ce Zhang},
	booktitle = {Proceedings of the 2nd International Workshop on In Memory Data Management and Analytics, IMDM 2014, Hangzhou, China},
	title = {Tradeoffs in Main-Memory Statistical Analytics from Impala to DimmWitted.},
	url = {http://www-db.in.tum.de/hosted/imdm2014/papers/bittorf.pdf},
	year = {2014}
}

@inproceedings{abc,
	author = {Srikrishna Sridhar and Stephen J. Wright and Christopher R{\'e} and Ji Liu and Victor Bittorf and Ce Zhang},
	booktitle = {Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States.},
	title = {An Approximate, Efficient LP Solver for LP Rounding.},
	url = {http://papers.nips.cc/paper/4990-an-approximate-efficient-lp-solver-for-lp-rounding},
	venue = {Lake Tahoe, Nevada, United States.},
	year = {2013}
}

@inproceedings{abc,
	author = {Michael Anderson and Dolan Antenucci and Victor Bittorf and Matthew Burgess and Michael J. Cafarella and Arun Kumar and Feng Niu and Yongjoo Park and Christopher R{\'e} and Ce Zhang},
	booktitle = {CIDR 2013, Sixth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA},
	title = {Brainwash: A Data System for Feature Engineering.},
	url = {http://www.cidrdb.org/cidr2013/Papers/CIDR13_Paper82.pdf},
	year = {2013}
}

@inproceedings{abc,
	abstract = {Many problems in machine learning can be solved by rounding the solution of an appropriate linear program (LP). This paper shows that we can recover solutions of comparable quality by rounding an approximate LP solution instead of the ex- act one. These approximate LP solutions can be computed efficiently by applying a parallel stochastic-coordinate-descent method to a quadratic-penalty formulation of the LP. We derive worst-case runtime and solution quality guarantees of this scheme using novel perturbation and convergence analysis. Our experiments demonstrate that on such combinatorial problems as vertex cover, independent set and multiway-cut, our approximate rounding scheme is up to an order of magnitude faster than Cplex (a commercial LP solver) while producing solutions of similar quality.},
	author = {Srikrishna Sridhar and Victor Bittorf and Ji Liu and Ce Zhang and Christopher R{\'e} and Stephen J. Wright},
	booktitle = {CoRR},
	title = {An Approximate, Efficient Solver for LP Rounding.},
	url = {http://arxiv.org/abs/1311.2661},
	venue = {-},
	year = {2013}
}