1: On Practical Algorithms for Entropy Estimation and the Improved Sample Complexity of Compressed Counting
2: n-Level Graph Partitioning
3: Efficient volume sampling for row/column subset selection
4: A General Framework for Graph Sparsification
5: Symmetric M-tree
6: Settling the Polynomial Learnability of Mixtures of Gaussians
7: A Sparse Johnson–Lindenstrauss Transform
8: Analysis of Basis Pursuit Via Capacity Sets
9: Cover times, blanket times, and majorizing measures
10: Optimal Data Placement on Networks With Constant Number of Clients
11: Chunky and Equal-Spaced Polynomial Multiplication
12: Simulating Parallel Algorithms in the MapReduce Framework with Applications to Parallel Computational Geometry
13: Modern Computer Arithmetic (version 0.5.1)
14: Polynomial Learning of Distribution Families
15: Graph Sparsification via Refinement Sampling
16: The stubborn problem is stubborn no more (a polynomial algorithm for 3-compatible colouring and the stubborn list partition problem)
17: Bandwidth and Distortion Revisited