`Travelled to:`

1 × China

1 × Finland

1 × United Kingdom

2 × USA

3 × Canada

`Collaborated with:`

J.Langford C.Tosh M.Telgarsky D.Hsu Y.Freund L.Cayton A.Beygelzimer D.Precup R.S.Sutton T.Batu R.Kumar R.Rubinfeld

`Talks about:`

learn (4) activ (3) approxim (2) euclidean (1) dimension (1) manifold (1) hierarch (1) gaussian (1) function (1) summari (1)

## Person: Sanjoy Dasgupta

### DBLP: Dasgupta:Sanjoy

### Contributed to:

### Wrote 9 papers:

- ICML-c2-2014-ToshD #bound
- Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians (CT, SD), pp. 1467–1475.
- ICML-2012-TelgarskyD #clustering
- Agglomerative Bregman Clustering (MT, SD), p. 132.
- ICML-2009-BeygelzimerDL #learning
- Importance weighted active learning (AB, SD, JL), pp. 49–56.
- ICML-2009-DasguptaL #learning #summary #tutorial
- Tutorial summary: Active learning (SD, JL), p. 18.
- ICML-2008-DasguptaH #learning
- Hierarchical sampling for active learning (SD, DH), pp. 208–215.
- STOC-2008-DasguptaF #random
- Random projection trees and low dimensional manifolds (SD, YF), pp. 537–546.
- ICML-2006-CaytonD #robust
- Robust Euclidean embedding (LC, SD), pp. 169–176.
- STOC-2002-BatuDKR #approximate #complexity
- The complexity of approximating entropy (TB, SD, RK, RR), pp. 678–687.
- ICML-2001-PrecupSD #approximate #difference #learning
- Off-Policy Temporal Difference Learning with Function Approximation (DP, RSS, SD), pp. 417–424.