| 1 |
Competitive Statistical Estimation With Strategic Data Sources
Westenbroek T, Dong R, Ratliff LJ, Sastry SS
IEEE Transactions on Automatic Control, 65(4), 1537, 2020 |
| 2 |
Assessing climate sensitivity of peak electricity load for resilient power systems planning and operation: A study applied to the Texas region
Alipour P, Mukherjee S, Nateghi R
Energy, 185, 1143, 2019 |
| 3 |
Computational modeling of biodiesel production using supercritical methanol
Baghban A
Energy Sources Part A-recovery Utilization and Environmental Effects, 41(1), 14, 2019 |
| 4 |
Probabilistic forecasting of day-ahead solar irradiance using quantile gradient boosting
Verbois H, Rusydi A, Thiery A
Solar Energy, 173, 313, 2018 |
| 5 |
An adsorbed gas estimation model for shale gas reservoirs via statistical learning
Chen YT, Jiang S, Zhang DX, Liu CY
Applied Energy, 197, 327, 2017 |
| 6 |
Data driven prediction models of energy use of appliances in a low-energy house
Candanedo LM, Feldheim V, Deramaix D
Energy and Buildings, 140, 81, 2017 |
| 7 |
Evaluation of statistical learning configurations for gridded solar irradiance forecasting
Gagne DJ, McGovern A, Haupt SE, Williams JK
Solar Energy, 150, 383, 2017 |
| 8 |
Using statistical learning to close two-fluid multiphase flow equations for bubbly flows in vertical channels
Ma M, Lu JC, Tryggvason G
International Journal of Multiphase Flow, 85, 336, 2016 |
| 9 |
On the Connection Between Compression Learning and Scenario Based Single-Stage and Cascading Optimization Problems
Margellos K, Prandini M, Lygeros J
IEEE Transactions on Automatic Control, 60(10), 2716, 2015 |
| 10 |
A statistical learning theory approach for uncertain linear and bilinear matrix inequalities
Chamanbaz M, Dabbene F, Tempo R, Venkataramanan V, Wang QG
Automatica, 50(6), 1617, 2014 |
