Travelled to:
1 × Australia
1 × Iceland
1 × Latvia
2 × United Kingdom
4 × USA
Collaborated with:
R.A.Servedio A.De C.Daskalakis S.Chan X.Sun C.H.Papadimitriou G.Pierrakos Y.Singer V.Feldman H.Liu M.Petracca L.P.Carloni J.Acharya C.Hegde J.Z.Li L.Schmidt H.K.Lee K.Matulef A.Wan P.Harsha A.Klivans R.Meka P.Raghavendra L.Tan
Talks about:
approxim (4) polynomi (3) effici (3) optim (3) distribut (2) algorithm (2) problem (2) sensit (2) near (2) threshold (1)
Person: Ilias Diakonikolas
DBLP: Diakonikolas:Ilias
Contributed to:
Wrote 10 papers:
- PODS-2015-AcharyaDHLS #algorithm #approximate #performance
- Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms (JA, ID, CH, JZL, LS), pp. 249–263.
- STOC-2014-ChanDSS #approximate #estimation #performance #polynomial
- Efficient density estimation via piecewise polynomial approximation (SoC, ID, RAS, XS), pp. 604–613.
- ICALP-v1-2013-DeDS #algorithm #analysis #difference #fourier #geometry #robust
- A Robust Khintchine Inequality, and Algorithms for Computing Optimal Constants in Fourier Analysis and High-Dimensional Geometry (AD, ID, RAS), pp. 376–387.
- ICALP-v1-2012-DeDS #problem
- The Inverse Shapley Value Problem (AD, ID, RAS), pp. 266–277.
- ICALP-v2-2012-DiakonikolasPPS #trade-off
- Efficiency-Revenue Trade-Offs in Auctions (ID, CHP, GP, YS), pp. 488–499.
- STOC-2012-DaskalakisDS #learning
- Learning poisson binomial distributions (CD, ID, RAS), pp. 709–728.
- STOC-2012-DeDFS #approximate #parametricity #problem
- Nearly optimal solutions for the chow parameters problem and low-weight approximation of halfspaces (AD, ID, VF, RAS), pp. 729–746.
- DAC-2011-LiuDPC #approximate #composition #design #set
- Supervised design space exploration by compositional approximation of Pareto sets (HYL, ID, MP, LPC), pp. 399–404.
- STOC-2010-DiakonikolasHKMRST #bound #polynomial
- Bounding the average sensitivity and noise sensitivity of polynomial threshold functions (ID, PH, AK, RM, PR, RAS, LYT), pp. 533–542.
- ICALP-A-2008-DiakonikolasLMSW #testing
- Efficiently Testing Sparse GF(2) Polynomials (ID, HKL, KM, RAS, AW), pp. 502–514.