`Travelled to:`

1 × Italy

1 × Slovenia

2 × Canada

5 × USA

`Collaborated with:`

R.E.Schapire ∅ S.Dasgupta L.Mason Y.Singer M.K.Warmuth R.D.Iyer P.Barlett W.S.Lee N.Cesa-Bianchi D.P.Helmbold D.Haussler M.J.Kearns D.Ron R.Rubinfeld L.Sellie

`Talks about:`

boost (4) algorithm (3) learn (3) random (2) effici (2) combin (2) tree (2) use (2) new (2) predictor (1)

## Person: Yoav Freund

### DBLP: Freund:Yoav

### Contributed to:

### Wrote 10 papers:

- KDD-2010-Freund
- Data winnowing (YF), pp. 3–4.
- ICML-2009-Freund #game studies #learning #online
- Invited talk: Drifting games, boosting and online learning (YF), p. 2.
- STOC-2008-DasguptaF #random
- Random projection trees and low dimensional manifolds (SD, YF), pp. 537–546.
- ICML-1999-FreundM #algorithm #learning
- The Alternating Decision Tree Learning Algorithm (YF, LM), pp. 124–133.
- ICML-1998-FreundISS #algorithm #performance
- An Efficient Boosting Algorithm for Combining Preferences (YF, RDI, RES, YS), pp. 170–178.
- ICML-1997-SchapireFBL #effectiveness
- Boosting the margin: A new explanation for the effectiveness of voting methods (RES, YF, PB, WSL), pp. 322–330.
- STOC-1997-FreundSSW #predict #using
- Using and Combining Predictors That Specialize (YF, RES, YS, MKW), pp. 334–343.
- ICML-1996-FreundS #algorithm
- Experiments with a New Boosting Algorithm (YF, RES), pp. 148–156.
- STOC-1993-Cesa-BianchiFHHSW #how
- How to use expert advice (NCB, YF, DPH, DH, RES, MKW), pp. 382–391.
- STOC-1993-FreundKRRSS #automaton #finite #learning #performance #random
- Efficient learning of typical finite automata from random walks (YF, MJK, DR, RR, RES, LS), pp. 315–324.