---
_id: '6526'
abstract:
- lang: eng
text: 'This paper studies the complexity of estimating Rényi divergences of discrete
distributions: p observed from samples and the baseline distribution q known a
priori. Extending the results of Acharya et al. (SODA''15) on estimating Rényi
entropy, we present improved estimation techniques together with upper and lower
bounds on the sample complexity. We show that, contrarily to estimating Rényi
entropy where a sublinear (in the alphabet size) number of samples suffices, the
sample complexity is heavily dependent on events occurring unlikely in q, and
is unbounded in general (no matter what an estimation technique is used). For
any divergence of integer order bigger than 1, we provide upper and lower bounds
on the number of samples dependent on probabilities of p and q (the lower bounds
hold for non-integer orders as well). We conclude that the worst-case sample complexity
is polynomial in the alphabet size if and only if the probabilities of q are non-negligible.
This gives theoretical insights into heuristics used in the applied literature
to handle numerical instability, which occurs for small probabilities of q. Our
result shows that they should be handled with care not only because of numerical
issues, but also because of a blow up in the sample complexity.'
article_number: '8006529'
author:
- first_name: Maciej
full_name: Skórski, Maciej
id: EC09FA6A-02D0-11E9-8223-86B7C91467DD
last_name: Skórski
citation:
ama: 'Skórski M. On the complexity of estimating Rènyi divergences. In: 2017
IEEE International Symposium on Information Theory (ISIT). IEEE; 2017. doi:10.1109/isit.2017.8006529'
apa: 'Skórski, M. (2017). On the complexity of estimating Rènyi divergences. In
2017 IEEE International Symposium on Information Theory (ISIT). Aachen,
Germany: IEEE. https://doi.org/10.1109/isit.2017.8006529'
chicago: Skórski, Maciej. “On the Complexity of Estimating Rènyi Divergences.” In
2017 IEEE International Symposium on Information Theory (ISIT). IEEE, 2017.
https://doi.org/10.1109/isit.2017.8006529.
ieee: M. Skórski, “On the complexity of estimating Rènyi divergences,” in 2017
IEEE International Symposium on Information Theory (ISIT), Aachen, Germany,
2017.
ista: 'Skórski M. 2017. On the complexity of estimating Rènyi divergences. 2017
IEEE International Symposium on Information Theory (ISIT). ISIT: International
Symposium on Information Theory, 8006529.'
mla: Skórski, Maciej. “On the Complexity of Estimating Rènyi Divergences.” 2017
IEEE International Symposium on Information Theory (ISIT), 8006529, IEEE,
2017, doi:10.1109/isit.2017.8006529.
short: M. Skórski, in:, 2017 IEEE International Symposium on Information Theory
(ISIT), IEEE, 2017.
conference:
end_date: 2017-06-30
location: Aachen, Germany
name: 'ISIT: International Symposium on Information Theory'
start_date: 2017-06-25
date_created: 2019-06-06T12:53:09Z
date_published: 2017-08-09T00:00:00Z
date_updated: 2021-01-12T08:07:53Z
day: '09'
department:
- _id: KrPi
doi: 10.1109/isit.2017.8006529
ec_funded: 1
external_id:
arxiv:
- '1702.01666'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1702.01666
month: '08'
oa: 1
oa_version: Preprint
project:
- _id: 258AA5B2-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '682815'
name: Teaching Old Crypto New Tricks
publication: 2017 IEEE International Symposium on Information Theory (ISIT)
publication_identifier:
isbn:
- '9781509040964'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: 1
status: public
title: On the complexity of estimating Rènyi divergences
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2017'
...
---
_id: '655'
abstract:
- lang: eng
text: 'The bacterial flagellum is a self-assembling nanomachine. The external flagellar
filament, several times longer than a bacterial cell body, is made of a few tens
of thousands subunits of a single protein: flagellin. A fundamental problem concerns
the molecular mechanism of how the flagellum grows outside the cell, where no
discernible energy source is available. Here, we monitored the dynamic assembly
of individual flagella using in situ labelling and real-time immunostaining of
elongating flagellar filaments. We report that the rate of flagellum growth, initially
~1,700 amino acids per second, decreases with length and that the previously proposed
chain mechanism does not contribute to the filament elongation dynamics. Inhibition
of the proton motive force-dependent export apparatus revealed a major contribution
of substrate injection in driving filament elongation. The combination of experimental
and mathematical evidence demonstrates that a simple, injection-diffusion mechanism
controls bacterial flagella growth outside the cell.'
article_number: e23136
author:
- first_name: Thibaud
full_name: Renault, Thibaud
last_name: Renault
- first_name: Anthony
full_name: Abraham, Anthony
last_name: Abraham
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Guillaume
full_name: Paradis, Guillaume
last_name: Paradis
- first_name: Simon
full_name: Rainville, Simon
last_name: Rainville
- first_name: Emmanuelle
full_name: Charpentier, Emmanuelle
last_name: Charpentier
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Yuhai
full_name: Tu, Yuhai
last_name: Tu
- first_name: Keiichi
full_name: Namba, Keiichi
last_name: Namba
- first_name: James
full_name: Keener, James
last_name: Keener
- first_name: Tohru
full_name: Minamino, Tohru
last_name: Minamino
- first_name: Marc
full_name: Erhardt, Marc
last_name: Erhardt
citation:
ama: Renault T, Abraham A, Bergmiller T, et al. Bacterial flagella grow through
an injection diffusion mechanism. eLife. 2017;6. doi:10.7554/eLife.23136
apa: Renault, T., Abraham, A., Bergmiller, T., Paradis, G., Rainville, S., Charpentier,
E., … Erhardt, M. (2017). Bacterial flagella grow through an injection diffusion
mechanism. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.23136
chicago: Renault, Thibaud, Anthony Abraham, Tobias Bergmiller, Guillaume Paradis,
Simon Rainville, Emmanuelle Charpentier, Calin C Guet, et al. “Bacterial Flagella
Grow through an Injection Diffusion Mechanism.” ELife. eLife Sciences Publications,
2017. https://doi.org/10.7554/eLife.23136.
ieee: T. Renault et al., “Bacterial flagella grow through an injection diffusion
mechanism,” eLife, vol. 6. eLife Sciences Publications, 2017.
ista: Renault T, Abraham A, Bergmiller T, Paradis G, Rainville S, Charpentier E,
Guet CC, Tu Y, Namba K, Keener J, Minamino T, Erhardt M. 2017. Bacterial flagella
grow through an injection diffusion mechanism. eLife. 6, e23136.
mla: Renault, Thibaud, et al. “Bacterial Flagella Grow through an Injection Diffusion
Mechanism.” ELife, vol. 6, e23136, eLife Sciences Publications, 2017, doi:10.7554/eLife.23136.
short: T. Renault, A. Abraham, T. Bergmiller, G. Paradis, S. Rainville, E. Charpentier,
C.C. Guet, Y. Tu, K. Namba, J. Keener, T. Minamino, M. Erhardt, ELife 6 (2017).
date_created: 2018-12-11T11:47:44Z
date_published: 2017-03-06T00:00:00Z
date_updated: 2021-01-12T08:07:55Z
day: '06'
ddc:
- '579'
department:
- _id: CaGu
doi: 10.7554/eLife.23136
file:
- access_level: open_access
checksum: 39e1c3e82ddac83a30422fa72fa1a383
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:08:53Z
date_updated: 2020-07-14T12:47:33Z
file_id: '4716'
file_name: IST-2017-904-v1+1_elife-23136-v2.pdf
file_size: 5520359
relation: main_file
- access_level: open_access
checksum: a6d542253028f52e00aa29739ddffe8f
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:08:54Z
date_updated: 2020-07-14T12:47:33Z
file_id: '4717'
file_name: IST-2017-904-v1+2_elife-23136-figures-v2.pdf
file_size: 11242920
relation: main_file
file_date_updated: 2020-07-14T12:47:33Z
has_accepted_license: '1'
intvolume: ' 6'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '03'
oa: 1
oa_version: Published Version
publication: eLife
publication_identifier:
issn:
- 2050084X
publication_status: published
publisher: eLife Sciences Publications
publist_id: '7082'
pubrep_id: '904'
quality_controlled: '1'
scopus_import: 1
status: public
title: Bacterial flagella grow through an injection diffusion mechanism
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 6
year: '2017'
...
---
_id: '657'
abstract:
- lang: eng
text: Plant organs are typically organized into three main tissue layers. The middle
ground tissue layer comprises the majority of the plant body and serves a wide
range of functions, including photosynthesis, selective nutrient uptake and storage,
and gravity sensing. Ground tissue patterning and maintenance in Arabidopsis are
controlled by a well-established gene network revolving around the key regulator
SHORT-ROOT (SHR). In contrast, it is completely unknown how ground tissue identity
is first specified from totipotent precursor cells in the embryo. The plant signaling
molecule auxin, acting through AUXIN RESPONSE FACTOR (ARF) transcription factors,
is critical for embryo patterning. The auxin effector ARF5/MONOPTEROS (MP) acts
both cell-autonomously and noncell-autonomously to control embryonic vascular
tissue formation and root initiation, respectively. Here we show that auxin response
and ARF activity cell-autonomously control the asymmetric division of the first
ground tissue cells. By identifying embryonic target genes, we show that MP transcriptionally
initiates the ground tissue lineage and acts upstream of the regulatory network
that controls ground tissue patterning and maintenance. Strikingly, whereas the
SHR network depends on MP, this MP function is, at least in part, SHR independent.
Our study therefore identifies auxin response as a regulator of ground tissue
specification in the embryonic root, and reveals that ground tissue initiation
and maintenance use different regulators and mechanisms. Moreover, our data provide
a framework for the simultaneous formation of multiple cell types by the same
transcriptional regulator.
author:
- first_name: Barbara
full_name: Möller, Barbara
last_name: Möller
- first_name: Colette
full_name: Ten Hove, Colette
last_name: Ten Hove
- first_name: Daoquan
full_name: Xiang, Daoquan
last_name: Xiang
- first_name: Nerys
full_name: Williams, Nerys
last_name: Williams
- first_name: Lorena
full_name: López, Lorena
last_name: López
- first_name: Saiko
full_name: Yoshida, Saiko
id: 2E46069C-F248-11E8-B48F-1D18A9856A87
last_name: Yoshida
- first_name: Margot
full_name: Smit, Margot
last_name: Smit
- first_name: Raju
full_name: Datla, Raju
last_name: Datla
- first_name: Dolf
full_name: Weijers, Dolf
last_name: Weijers
citation:
ama: Möller B, Ten Hove C, Xiang D, et al. Auxin response cell autonomously controls
ground tissue initiation in the early arabidopsis embryo. PNAS. 2017;114(12):E2533-E2539.
doi:10.1073/pnas.1616493114
apa: Möller, B., Ten Hove, C., Xiang, D., Williams, N., López, L., Yoshida, S.,
… Weijers, D. (2017). Auxin response cell autonomously controls ground tissue
initiation in the early arabidopsis embryo. PNAS. National Academy of Sciences.
https://doi.org/10.1073/pnas.1616493114
chicago: Möller, Barbara, Colette Ten Hove, Daoquan Xiang, Nerys Williams, Lorena
López, Saiko Yoshida, Margot Smit, Raju Datla, and Dolf Weijers. “Auxin Response
Cell Autonomously Controls Ground Tissue Initiation in the Early Arabidopsis Embryo.”
PNAS. National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1616493114.
ieee: B. Möller et al., “Auxin response cell autonomously controls ground
tissue initiation in the early arabidopsis embryo,” PNAS, vol. 114, no.
12. National Academy of Sciences, pp. E2533–E2539, 2017.
ista: Möller B, Ten Hove C, Xiang D, Williams N, López L, Yoshida S, Smit M, Datla
R, Weijers D. 2017. Auxin response cell autonomously controls ground tissue initiation
in the early arabidopsis embryo. PNAS. 114(12), E2533–E2539.
mla: Möller, Barbara, et al. “Auxin Response Cell Autonomously Controls Ground Tissue
Initiation in the Early Arabidopsis Embryo.” PNAS, vol. 114, no. 12, National
Academy of Sciences, 2017, pp. E2533–39, doi:10.1073/pnas.1616493114.
short: B. Möller, C. Ten Hove, D. Xiang, N. Williams, L. López, S. Yoshida, M. Smit,
R. Datla, D. Weijers, PNAS 114 (2017) E2533–E2539.
date_created: 2018-12-11T11:47:45Z
date_published: 2017-03-21T00:00:00Z
date_updated: 2021-01-12T08:08:02Z
day: '21'
department:
- _id: JiFr
doi: 10.1073/pnas.1616493114
external_id:
pmid:
- '28265057'
intvolume: ' 114'
issue: '12'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5373392/
month: '03'
oa: 1
oa_version: Submitted Version
page: E2533 - E2539
pmid: 1
publication: PNAS
publication_identifier:
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
publist_id: '7076'
quality_controlled: '1'
scopus_import: 1
status: public
title: Auxin response cell autonomously controls ground tissue initiation in the early
arabidopsis embryo
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 114
year: '2017'
...
---
_id: '656'
abstract:
- lang: eng
text: Human neurons transplanted into a mouse model for Alzheimer’s disease show
human-specific vulnerability to β-amyloid plaques and may help to identify new
therapeutic targets.
article_number: eaam9867
author:
- first_name: Gaia
full_name: Novarino, Gaia
id: 3E57A680-F248-11E8-B48F-1D18A9856A87
last_name: Novarino
orcid: 0000-0002-7673-7178
citation:
ama: Novarino G. Modeling Alzheimer’s disease in mice with human neurons. Science
Translational Medicine. 2017;9(381). doi:10.1126/scitranslmed.aam9867
apa: Novarino, G. (2017). Modeling Alzheimer’s disease in mice with human neurons.
Science Translational Medicine. American Association for the Advancement
of Science. https://doi.org/10.1126/scitranslmed.aam9867
chicago: Novarino, Gaia. “Modeling Alzheimer’s Disease in Mice with Human Neurons.”
Science Translational Medicine. American Association for the Advancement
of Science, 2017. https://doi.org/10.1126/scitranslmed.aam9867.
ieee: G. Novarino, “Modeling Alzheimer’s disease in mice with human neurons,” Science
Translational Medicine, vol. 9, no. 381. American Association for the Advancement
of Science, 2017.
ista: Novarino G. 2017. Modeling Alzheimer’s disease in mice with human neurons.
Science Translational Medicine. 9(381), eaam9867.
mla: Novarino, Gaia. “Modeling Alzheimer’s Disease in Mice with Human Neurons.”
Science Translational Medicine, vol. 9, no. 381, eaam9867, American Association
for the Advancement of Science, 2017, doi:10.1126/scitranslmed.aam9867.
short: G. Novarino, Science Translational Medicine 9 (2017).
date_created: 2018-12-11T11:47:45Z
date_published: 2017-03-15T00:00:00Z
date_updated: 2021-01-12T08:07:59Z
day: '15'
department:
- _id: GaNo
doi: 10.1126/scitranslmed.aam9867
intvolume: ' 9'
issue: '381'
language:
- iso: eng
month: '03'
oa_version: None
publication: Science Translational Medicine
publication_identifier:
issn:
- '19466234'
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '7079'
quality_controlled: '1'
scopus_import: 1
status: public
title: Modeling Alzheimer's disease in mice with human neurons
type: journal_article
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
volume: 9
year: '2017'
...
---
_id: '658'
abstract:
- lang: eng
text: 'With the accelerated development of robot technologies, control becomes one
of the central themes of research. In traditional approaches, the controller,
by its internal functionality, finds appropriate actions on the basis of specific
objectives for the task at hand. While very successful in many applications, self-organized
control schemes seem to be favored in large complex systems with unknown dynamics
or which are difficult to model. Reasons are the expected scalability, robustness,
and resilience of self-organizing systems. The paper presents a self-learning
neurocontroller based on extrinsic differential plasticity introduced recently,
applying it to an anthropomorphic musculoskeletal robot arm with attached objects
of unknown physical dynamics. The central finding of the paper is the following
effect: by the mere feedback through the internal dynamics of the object, the
robot is learning to relate each of the objects with a very specific sensorimotor
pattern. Specifically, an attached pendulum pilots the arm into a circular motion,
a half-filled bottle produces axis oriented shaking behavior, a wheel is getting
rotated, and wiping patterns emerge automatically in a table-plus-brush setting.
By these object-specific dynamical patterns, the robot may be said to recognize
the object''s identity, or in other words, it discovers dynamical affordances
of objects. Furthermore, when including hand coordinates obtained from a camera,
a dedicated hand-eye coordination self-organizes spontaneously. These phenomena
are discussed from a specific dynamical system perspective. Central is the dedicated
working regime at the border to instability with its potentially infinite reservoir
of (limit cycle) attractors "waiting" to be excited. Besides converging
toward one of these attractors, variate behavior is also arising from a self-induced
attractor morphing driven by the learning rule. We claim that experimental investigations
with this anthropomorphic, self-learning robot not only generate interesting and
potentially useful behaviors, but may also help to better understand what subjective
human muscle feelings are, how they can be rooted in sensorimotor patterns, and
how these concepts may feed back on robotics.'
article_number: '00008'
article_processing_charge: Yes
author:
- first_name: Ralf
full_name: Der, Ralf
last_name: Der
- first_name: Georg S
full_name: Martius, Georg S
id: 3A276B68-F248-11E8-B48F-1D18A9856A87
last_name: Martius
citation:
ama: Der R, Martius GS. Self organized behavior generation for musculoskeletal robots.
Frontiers in Neurorobotics. 2017;11(MAR). doi:10.3389/fnbot.2017.00008
apa: Der, R., & Martius, G. S. (2017). Self organized behavior generation for
musculoskeletal robots. Frontiers in Neurorobotics. Frontiers Research
Foundation. https://doi.org/10.3389/fnbot.2017.00008
chicago: Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for
Musculoskeletal Robots.” Frontiers in Neurorobotics. Frontiers Research
Foundation, 2017. https://doi.org/10.3389/fnbot.2017.00008.
ieee: R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal
robots,” Frontiers in Neurorobotics, vol. 11, no. MAR. Frontiers Research
Foundation, 2017.
ista: Der R, Martius GS. 2017. Self organized behavior generation for musculoskeletal
robots. Frontiers in Neurorobotics. 11(MAR), 00008.
mla: Der, Ralf, and Georg S. Martius. “Self Organized Behavior Generation for Musculoskeletal
Robots.” Frontiers in Neurorobotics, vol. 11, no. MAR, 00008, Frontiers
Research Foundation, 2017, doi:10.3389/fnbot.2017.00008.
short: R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017).
date_created: 2018-12-11T11:47:45Z
date_published: 2017-03-16T00:00:00Z
date_updated: 2021-01-12T08:08:04Z
day: '16'
ddc:
- '006'
department:
- _id: ChLa
- _id: GaTk
doi: 10.3389/fnbot.2017.00008
ec_funded: 1
file:
- access_level: open_access
checksum: b1bc43f96d1df3313c03032c2a46388d
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:18:49Z
date_updated: 2020-07-14T12:47:33Z
file_id: '5371'
file_name: IST-2017-903-v1+1_fnbot-11-00008.pdf
file_size: 8439566
relation: main_file
file_date_updated: 2020-07-14T12:47:33Z
has_accepted_license: '1'
intvolume: ' 11'
issue: MAR
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Frontiers in Neurorobotics
publication_identifier:
issn:
- '16625218'
publication_status: published
publisher: Frontiers Research Foundation
publist_id: '7078'
pubrep_id: '903'
quality_controlled: '1'
scopus_import: 1
status: public
title: Self organized behavior generation for musculoskeletal robots
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2017'
...