Monthly Archives: February 2018

Statseminars Stat & Data Science Seminar, Speaker: Aaditya Ramdas, Monday, 2/26 @ 4:15pm

DEPARTMENT OF STATISTICS AND DATA SCIENCE SEMINAR

Date: Monday, February 26, 2018

Time: 4:15pm – 5:15pm

Place: 24 Hillhouse Avenue, Rm. 107

Seminar Speaker: Aaditya Ramdas

University of California, Berkeley, http://people.eecs.berkeley.edu/~aramdas/

Title: Interactive algorithms for multiple hypothesis testing

Abstract: Data science is at a crossroads. Each year, thousands of new data scientists are entering science and technology, after a broad training in a variety of fields. Modern data science is often exploratory in nature, with datasets being collected and dissected in an interactive manner. Classical guarantees that accompany many statistical methods are often invalidated by their non-standard interactive use, resulting in an underestimated risk of falsely discovering correlations or patterns. It is a pressing challenge to upgrade existing tools, or create new ones, that are robust to involving a human-in-the-loop. In this talk, I will describe two new advances that enable some amount of interactivity while testing multiple hypotheses, and control the resulting selection bias. I will first introduce a new framework, STAR, that uses partial masking to divide the available information into two parts, one for selecting a set of potential discoveries, and the other for inference on the selected set. I will then show that it is possible to flip the traditional roles of the algorithm and the scientist, allowing the scientist to make post-hoc decisions after seeing the realization of an algorithm on the data. The theoretical basis for both advances is founded in the theory of martingales : in the first, the user defines the martingale and associated filtration interactively, and in the second, we move from optional stopping to optional spotting by proving uniform concentration bounds on relevant martingales.

This talk will feature joint work with (alphabetically) Rina Barber, Jianbo Chen, Will Fithian, Kevin Jamieson, Michael Jordan, Eugene Katsevich, Lihua Lei, Max Rabinovich, Martin Wainwright, Fanny Yang and Tijana Zrnic. Bio : Aaditya Ramdas is a postdoctoral researcher in Statistics and EECS at UC Berkeley, advised by Michael Jordan and Martin Wainwright. He finished his PhD in Statistics and Machine Learning at CMU, advised by Larry Wasserman and Aarti Singh, winning the Best Thesis Award in Statistics. A lot of his research focuses on modern aspects of reproducibility in science and technology — involving statistical testing and false discovery rate control in static and dynamic settings.

4:00 p.m. Refreshments in Common Room, 24 Hillhouse Avenue

4:15p.m. – 5:15p.m. Seminar, Room 107, 24 Hillhouse Avenue

For more details and upcoming events visit our website at
http://statistics.yale.edu/ .

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farnam disk usage

total 4.93542E+11 of 600 TB
gg487 80346153088
sl857 42453918080
fn64 37230865408
jx98 34102180352
mg888 31884811008
jz435 27793173504
tg397 26743508608
sk972 21909421952
pse5 20333742208
sl2373 15417125248
dl598 15304594048
cs784 13923634560
mr724 11768326784
ll426 8905029760
sl847 8821790592
wum2 8420884352
pmm49 8177639424
jad248 7989755008
yy222 6347266176
rrk24 6182451584
yf9 5816445952
hm444 5719293568
mihali 5459016704
lc848 4090249984
meg98 3984611584
ah633 3367398912
bp272 2906803456
xk4 2393468032
jjl86 1928689024
rdb9 1763952640
msp48 1748680320
as2665 1596345472
ky26 1583088768
ml724 1557992448
jl56 1480538368
ha275 1467031936
jw2394 1423484800
sb238 1275168128
gf3 1189340928
jrb97 1012897664
cy288 876665856
slw67 788305152
pdm32 752088448
lh372 671649152
jsr59 592016256
as898 506352512
dc547 424654976
mpw6 385383040
hz244 374372096
km735 337744640
nb23 324053504
ls926 314810880
keckadmins 265108480
aa544 249558400
xl348 237337088
simen 163574272
xz374 162198144
lr579 159751424
yf95 150772480
nmb38 115795456
jjl83 109213440
mas343 96425216
yk336 95688832
williams 95688832
xc279 85381888
zl222 68034176
wb244 63682432
rka24 59127808
yy448 46536704
aa65 44632832
zc264 43432192
gene760 33406080
zhao 25241600
amg89 21919360
co254 21889920
an377 19965312
xm24 19335680
jc2296 17970560
jw72 17455616
njc2 16694016
mx55 11160960
root 9156608
jk935 6167936
cc59 4636672
law72 3522560
shuch 3039616
yz464 1122176
gene760_2016 475520
bab99 387584
tl444 326144
dr395 185472
jhq4 115584
mj332 60160
rm658 4096
jjp76 3968

farnam disk usage

total 4.74044E+11 of 600TB
gg487 68627853184
sl857 40207958400
fn64 37218993792
mg888 31879822848
jx98 28932878592
jz435 27642752768
tg397 26743508608
sk972 21890823936
pse5 20578109440
sl2373 15417109888
dl598 15304594048
cs784 13769373824
mr724 11768326784
ll426 8905029760
sl847 8821790592
wum2 8387013376
pmm49 8177639424
jad248 7989755008
yy222 6347266176
rrk24 6182451584
yf9 5816445952
hm444 5719131264
mihali 5459016704
lc848 4090249984
meg98 3978573696
ah633 3367398912
bp272 2906803456
xk4 2392460544
rdb9 1763952640
msp48 1748680320
jjl86 1744928512
as2665 1596345472
ky26 1583088768
ml724 1557992448
jl56 1480538368
ha275 1467031936
jw2394 1423484800
sb238 1275168128
gf3 1189340928
jrb97 1012897664
cy288 876662528
slw67 785871360
pdm32 751971072
lh372 671649152
jsr59 592016256
as898 506352512
dc547 424609664
mpw6 385383040
hz244 374372096
km735 337744640
nb23 324053504
ls926 314810880
keckadmins 265108480
aa544 249558400
xl348 237337088
simen 163574272
xz374 162198144
lr579 159751424
yf95 150772480
nmb38 115795456
jjl83 109213440
mas343 96425216
yk336 95688832
williams 95688832
xc279 85381888
zl222 68034176
wb244 63682432
rka24 59127808
yy448 46536704
aa65 44632832
gene760 33406080
zhao 25241600
amg89 21919360
co254 21889920
an377 19965312
xm24 19335680
jc2296 17970560
jw72 17455616
njc2 16694016
mx55 11160960
root 9156608
jk935 6167936
zc264 5485440
cc59 4636672
shuch 3039616
yz464 1122176
gene760_2016 475520
bab99 387584
tl444 326144
dr395 185472
mj332 60160
rm658 4096
jjp76 3968

JClub by BW on “3D clusters of somatic mutations in cancer reveal numerous rare mutations as functional targets”, Genome Medicine

3D clusters of somatic mutations…reveal numerous rare mutations as functional targets
https://GenomeMedicine.BiomedCentral.com/articles/10.1186/s13073-016-0393-x Introduces 3DHotSpots, which is one of a number of recent approaches (incl. CLUMPS, Hotspot3D, Mutation3D & HotMAPS) for finding groupings of somatic SNVs via structure