Empirical Methods for CS : Reading List

[1] Peter J. Denning. Is computer science science? Communications of the ACM, 48(4), 2005. [2] Craig Loehle. A guide to increased creativity in research—inspiration or perspiration? Bioscience, 40(2), 1990. [3] Walter F. Tichy. Should computer scientists experiment more? Computer, 31(5), 2002. [4] Duncan J. Watts and Steven H. Strogatz. Collective dynamics of ‘small-world’ networks. Nature, 393:440–442, June 1998. [5] Albert-Laszlo Barabasi and Reka Albert. Emergence of scaling in random networks. Science, 286:509– 512, October 1999. [6] George H. John. Robust decision trees: Removing outliers from databases. In Proc. KDD, 1995. [7] Tim Oates and David Jensen. The effects of training set size on decision tree complexity. In Proc. ICML, 1997. [8] Tim Oates and David Jensen. Toward a theoretical understanding of why and when decision tree pruning algorimths fail. In Proc. AAAI, 1999. [9] Sally Floyd and Van Jacobson. The synchronization of periodic routing messages. IEEE/ACM Transactions on Networking, 2, 1994. [10] John P. A. Ioannidis. Why most published research findings are false. PLoS Medicine, 2(8), 2005. [11] Amos Tversky and Daniel Kahneman. Judgment under uncertainty: heuristics and biases. Science, 185(4157):1124–1131, 1974. [12] Lars Backstrom, Dan Huttenlocker, Jon Kleinberg, and Xiangyang Lan. Group formation in large social networks: Membership, growth, and evolution. In Proc. KDD, 2006. [13] Pedro Domingos and Michael Pazzani. On the optimality of the simple Bayesian classifier under zero-one loss. Machine Learning, 29:103–130, 1997. [14] Susan Dumais, Edward Cutrell, JJ Cadiz, Gavin Jancke, Raman Sarin, and Daniel C. Robbins. Stuff i’ve seen: a system for personal information retrieval and re-use. In Proc. SIGIR, 2003. [15] Susan Dumais, Edward Cutrell, and Hao Chen. Optimizing search by showing results in context. In Proc. SIGCHI, 2001. [16] Matthew Hertz and Emery D. Berger. Quantifying the performance of garbage collection vs explicit memory management. In Proc. OOPSLA, 2005. [17] David D. Jensen and Paul R. Cohen. Multiple comparisons in induction algorithms. Machine Learning, 38:309–338, 2000. [18] Stephen M. Blackburn et al. Wake up and smell the coffee: evaluation methodology for the 21st century. Communications of the ACM, 51(8), 2008. [19] Marc Liberatore, Brian Neil Levine, and Chadi Barakat. Maximizing transfer opportunities in bluetooth dtns. In Proc. CoNEXT, 2006. [20] Tony Hey, Stewart Tansley, and Kristin Tolle, editors. The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research, 2009. [21] Scott Kirkpatrick and Bart Selman. Critical behavior in the satisfiability of random boolean expressions. Science, 264:1297–1301, 1994.