Israeli Statistical Association annual meeting (2018) -  presentations


Link to program


Applied  Data  Science  (Hebrew)

Chair:  Shlomi Lifshits


Ronny Lempel,  Outbrain

Statistical  Estimation  by Non-Standard  Adaptations  of Standard  Algorithms


Oren Glickman, Bar-Ilan  University

Using  Hebrew  Twitter  Word Embedding  in  Statistical Learning  Models


Moni Shahar,  Intuit

Data  Science  Problems  in Software  for  Personal  Finance


Roy Yadoo,  SimilarWeb

Panel  Based  Website and  Mobile  Applications Traffic  Estimation


Causal  Inference  (English)

Chair:  Ruth Heller


Roee Gutman, Brown  University

Robust  Estimation  of  Causal Effects  to  Evaluate  the  Effects of  Opioids  versus  NSAIDS  on Persistent  Pain


Uri Shalit, Technion

When  and  How  Should One  Use  Deep  Learning  for Causal  Inference


Noa Dagan, Clalit  Research  Institute

Determining  Individualized Causal  Treatment  Effects  – Shifting  the  Focus  from  the Statistical  Challenge  to Practical  Usability


Tal El-Hay, IBM  Research

Adversarial  Balancing  for Causal inference

Official  Statistics (Hebrew) 

Chair:  Luisa Burk


Ahmad Hleihel, Central  Bureau  of  Statistics 

Social  Statistics  in  the  Future


David Maagan, Central  Bureau  of  Statistics Development  of  Socio- Economic  Index  for  Students  in the  Education  System


Eitan Greenstein, Central  Bureau  of  Statistics

Post-Stratification,  Non- Response  and  Non-Parametric Empirical  Bayes


Natalia Tsibel, Central  Bureau  of  Statistics

Peripherality  Index  2015

Theoretical  Data  Science (English)

Chair:  Yuval Benjamini


Emilio Porcu, University  of  Newcastle,  UK

Random  Fields  Evolving Temporally  over  Spheres


Itai Dattner, Haifa  University

Application  of  One-Step Method  to  Parameter Estimation  in  ODE  Models


Marina Bogomolov, Technion

Testing  Hypotheses  on  a  Tree: New  Error  Rates  and Controlling  Strategies


Or Zuk, The  Hebrew  University of  Jerusalem

Testing  Independence  with Biased  Sampling

Deep  Learning  (Hebrew)

Chair:  Itai Dattner


David Golan, Technion  and  Viz.ai

A  Statistician's  Intro  to Deep  Learning


Naftali Tishby,  The  Hebrew University  of  Jerusalem

Information  Theory  of Deep  Learning: What  do  the  Layers  of  Deep Neural  Networks  Represent?


Raja Giryes,  Tel  Aviv  University

On  the  Generalization Properties  of  Deep Neural  Networks


Yarin Gal,  Oxford  University

Bayesian  Deep  Learning

Biostatistics  (English) In  collaboration  with  EMR-IBS

Chair:  Havi Murad


Martin Posch, Medical  University  of  Vienna

Subgroup  Identification  in Clinical  Trials  via  the  Predicted

 individual  Treatment  Effect


Shai Carmi, The  Hebrew University  of  Jerusalem

New  applications  of  Hidden Markov  Models  in  Genetics


Philip Tzvi Reiss, Haifa  University

Functional  Principal  Component

 Analysis  with  Applications  to Experience  Sampling  Data


Ruth Heller, Tel  Aviv  University

Inference  Following  Aggregated Association  Tests