---
_id: '5959'
abstract:
- lang: eng
text: Formalizing properties of systems with continuous dynamics is a challenging
task. In this paper, we propose a formal framework for specifying and monitoring
rich temporal properties of real-valued signals. We introduce signal first-order
logic (SFO) as a specification language that combines first-order logic with linear-real
arithmetic and unary function symbols interpreted as piecewise-linear signals.
We first show that while the satisfiability problem for SFO is undecidable, its
membership and monitoring problems are decidable. We develop an offline monitoring
procedure for SFO that has polynomial complexity in the size of the input trace
and the specification, for a fixed number of quantifiers and function symbols.
We show that the algorithm has computation time linear in the size of the input
trace for the important fragment of bounded-response specifications interpreted
over input traces with finite variability. We can use our results to extend signal
temporal logic with first-order quantifiers over time and value parameters, while
preserving its efficient monitoring. We finally demonstrate the practical appeal
of our logic through a case study in the micro-electronics domain.
article_processing_charge: No
author:
- first_name: Alexey
full_name: Bakhirkin, Alexey
last_name: Bakhirkin
- first_name: Thomas
full_name: Ferrere, Thomas
id: 40960E6E-F248-11E8-B48F-1D18A9856A87
last_name: Ferrere
orcid: 0000-0001-5199-3143
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000−0002−2985−7724
- first_name: Deian
full_name: Nickovicl, Deian
last_name: Nickovicl
citation:
ama: 'Bakhirkin A, Ferrere T, Henzinger TA, Nickovicl D. Keynote: The first-order
logic of signals. In: 2018 International Conference on Embedded Software.
IEEE; 2018:1-10. doi:10.1109/emsoft.2018.8537203'
apa: 'Bakhirkin, A., Ferrere, T., Henzinger, T. A., & Nickovicl, D. (2018).
Keynote: The first-order logic of signals. In 2018 International Conference
on Embedded Software (pp. 1–10). Turin, Italy: IEEE. https://doi.org/10.1109/emsoft.2018.8537203'
chicago: 'Bakhirkin, Alexey, Thomas Ferrere, Thomas A Henzinger, and Deian Nickovicl.
“Keynote: The First-Order Logic of Signals.” In 2018 International Conference
on Embedded Software, 1–10. IEEE, 2018. https://doi.org/10.1109/emsoft.2018.8537203.'
ieee: 'A. Bakhirkin, T. Ferrere, T. A. Henzinger, and D. Nickovicl, “Keynote: The
first-order logic of signals,” in 2018 International Conference on Embedded
Software, Turin, Italy, 2018, pp. 1–10.'
ista: 'Bakhirkin A, Ferrere T, Henzinger TA, Nickovicl D. 2018. Keynote: The first-order
logic of signals. 2018 International Conference on Embedded Software. EMSOFT:
International Conference on Embedded Software, 1–10.'
mla: 'Bakhirkin, Alexey, et al. “Keynote: The First-Order Logic of Signals.” 2018
International Conference on Embedded Software, IEEE, 2018, pp. 1–10, doi:10.1109/emsoft.2018.8537203.'
short: A. Bakhirkin, T. Ferrere, T.A. Henzinger, D. Nickovicl, in:, 2018 International
Conference on Embedded Software, IEEE, 2018, pp. 1–10.
conference:
end_date: 2018-10-05
location: Turin, Italy
name: 'EMSOFT: International Conference on Embedded Software'
start_date: 2018-09-30
date_created: 2019-02-13T09:19:28Z
date_published: 2018-09-30T00:00:00Z
date_updated: 2023-09-19T10:41:29Z
day: '30'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1109/emsoft.2018.8537203
external_id:
isi:
- '000492828500005'
file:
- access_level: open_access
checksum: 234a33ad9055b3458fcdda6af251b33a
content_type: application/pdf
creator: dernst
date_created: 2020-05-14T16:01:29Z
date_updated: 2020-07-14T12:47:13Z
file_id: '7839'
file_name: 2018_EMSOFT_Bakhirkin.pdf
file_size: 338006
relation: main_file
file_date_updated: 2020-07-14T12:47:13Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 1-10
project:
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S 11407_N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 2018 International Conference on Embedded Software
publication_identifier:
isbn:
- '9781538655603'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Keynote: The first-order logic of signals'
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2018'
...
---
_id: '5962'
abstract:
- lang: eng
text: Stochastic Gradient Descent (SGD) is a fundamental algorithm in machine learning,
representing the optimization backbone for training several classic models, from
regression to neural networks. Given the recent practical focus on distributed
machine learning, significant work has been dedicated to the convergence properties
of this algorithm under the inconsistent and noisy updates arising from execution
in a distributed environment. However, surprisingly, the convergence properties
of this classic algorithm in the standard shared-memory model are still not well-understood.
In this work, we address this gap, and provide new convergence bounds for lock-free
concurrent stochastic gradient descent, executing in the classic asynchronous
shared memory model, against a strong adaptive adversary. Our results give improved
upper and lower bounds on the "price of asynchrony'' when executing the fundamental
SGD algorithm in a concurrent setting. They show that this classic optimization
tool can converge faster and with a wider range of parameters than previously
known under asynchronous iterations. At the same time, we exhibit a fundamental
trade-off between the maximum delay in the system and the rate at which SGD can
converge, which governs the set of parameters under which this algorithm can still
work efficiently.
article_processing_charge: No
author:
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
- first_name: Christopher
full_name: De Sa, Christopher
last_name: De Sa
- first_name: Nikola H
full_name: Konstantinov, Nikola H
id: 4B9D76E4-F248-11E8-B48F-1D18A9856A87
last_name: Konstantinov
citation:
ama: 'Alistarh D-A, De Sa C, Konstantinov NH. The convergence of stochastic gradient
descent in asynchronous shared memory. In: Proceedings of the 2018 ACM Symposium
on Principles of Distributed Computing - PODC ’18. ACM Press; 2018:169-178.
doi:10.1145/3212734.3212763'
apa: 'Alistarh, D.-A., De Sa, C., & Konstantinov, N. H. (2018). The convergence
of stochastic gradient descent in asynchronous shared memory. In Proceedings
of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18
(pp. 169–178). Egham, United Kingdom: ACM Press. https://doi.org/10.1145/3212734.3212763'
chicago: Alistarh, Dan-Adrian, Christopher De Sa, and Nikola H Konstantinov. “The
Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory.” In
Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing
- PODC ’18, 169–78. ACM Press, 2018. https://doi.org/10.1145/3212734.3212763.
ieee: D.-A. Alistarh, C. De Sa, and N. H. Konstantinov, “The convergence of stochastic
gradient descent in asynchronous shared memory,” in Proceedings of the 2018
ACM Symposium on Principles of Distributed Computing - PODC ’18, Egham, United
Kingdom, 2018, pp. 169–178.
ista: 'Alistarh D-A, De Sa C, Konstantinov NH. 2018. The convergence of stochastic
gradient descent in asynchronous shared memory. Proceedings of the 2018 ACM Symposium
on Principles of Distributed Computing - PODC ’18. PODC: Principles of Distributed
Computing, 169–178.'
mla: Alistarh, Dan-Adrian, et al. “The Convergence of Stochastic Gradient Descent
in Asynchronous Shared Memory.” Proceedings of the 2018 ACM Symposium on Principles
of Distributed Computing - PODC ’18, ACM Press, 2018, pp. 169–78, doi:10.1145/3212734.3212763.
short: D.-A. Alistarh, C. De Sa, N.H. Konstantinov, in:, Proceedings of the 2018
ACM Symposium on Principles of Distributed Computing - PODC ’18, ACM Press, 2018,
pp. 169–178.
conference:
end_date: 2018-07-27
location: Egham, United Kingdom
name: 'PODC: Principles of Distributed Computing'
start_date: 2018-07-23
date_created: 2019-02-13T09:58:58Z
date_published: 2018-07-23T00:00:00Z
date_updated: 2023-09-19T10:42:53Z
day: '23'
department:
- _id: DaAl
doi: 10.1145/3212734.3212763
external_id:
arxiv:
- '1803.08841'
isi:
- '000458186900022'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1803.08841
month: '07'
oa: 1
oa_version: Preprint
page: 169-178
publication: Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing -
PODC '18
publication_identifier:
isbn:
- '9781450357951'
publication_status: published
publisher: ACM Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: The convergence of stochastic gradient descent in asynchronous shared memory
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2018'
...
---
_id: '5860'
abstract:
- lang: eng
text: 'A major problem for evolutionary theory is understanding the so-called open-ended
nature of evolutionary change, from its definition to its origins. Open-ended
evolution (OEE) refers to the unbounded increase in complexity that seems to characterize
evolution on multiple scales. This property seems to be a characteristic feature
of biological and technological evolution and is strongly tied to the generative
potential associated with combinatorics, which allows the system to grow and expand
their available state spaces. Interestingly, many complex systems presumably displaying
OEE, from language to proteins, share a common statistical property: the presence
of Zipf''s Law. Given an inventory of basic items (such as words or protein domains)
required to build more complex structures (sentences or proteins) Zipf''s Law
tells us that most of these elements are rare whereas a few of them are extremely
common. Using algorithmic information theory, in this paper we provide a fundamental
definition for open-endedness, which can be understood as postulates. Its statistical
counterpart, based on standard Shannon information theory, has the structure of
a variational problem which is shown to lead to Zipf''s Law as the expected consequence
of an evolutionary process displaying OEE. We further explore the problem of information
conservation through an OEE process and we conclude that statistical information
(standard Shannon information) is not conserved, resulting in the paradoxical
situation in which the increase of information content has the effect of erasing
itself. We prove that this paradox is solved if we consider non-statistical forms
of information. This last result implies that standard information theory may
not be a suitable theoretical framework to explore the persistence and increase
of the information content in OEE systems.'
article_number: '20180395'
article_processing_charge: No
author:
- first_name: Bernat
full_name: Corominas-Murtra, Bernat
id: 43BE2298-F248-11E8-B48F-1D18A9856A87
last_name: Corominas-Murtra
orcid: 0000-0001-9806-5643
- first_name: Luís F.
full_name: Seoane, Luís F.
last_name: Seoane
- first_name: Ricard
full_name: Solé, Ricard
last_name: Solé
citation:
ama: Corominas-Murtra B, Seoane LF, Solé R. Zipf’s Law, unbounded complexity and
open-ended evolution. Journal of the Royal Society Interface. 2018;15(149).
doi:10.1098/rsif.2018.0395
apa: Corominas-Murtra, B., Seoane, L. F., & Solé, R. (2018). Zipf’s Law, unbounded
complexity and open-ended evolution. Journal of the Royal Society Interface.
Royal Society Publishing. https://doi.org/10.1098/rsif.2018.0395
chicago: Corominas-Murtra, Bernat, Luís F. Seoane, and Ricard Solé. “Zipf’s Law,
Unbounded Complexity and Open-Ended Evolution.” Journal of the Royal Society
Interface. Royal Society Publishing, 2018. https://doi.org/10.1098/rsif.2018.0395.
ieee: B. Corominas-Murtra, L. F. Seoane, and R. Solé, “Zipf’s Law, unbounded complexity
and open-ended evolution,” Journal of the Royal Society Interface, vol.
15, no. 149. Royal Society Publishing, 2018.
ista: Corominas-Murtra B, Seoane LF, Solé R. 2018. Zipf’s Law, unbounded complexity
and open-ended evolution. Journal of the Royal Society Interface. 15(149), 20180395.
mla: Corominas-Murtra, Bernat, et al. “Zipf’s Law, Unbounded Complexity and Open-Ended
Evolution.” Journal of the Royal Society Interface, vol. 15, no. 149, 20180395,
Royal Society Publishing, 2018, doi:10.1098/rsif.2018.0395.
short: B. Corominas-Murtra, L.F. Seoane, R. Solé, Journal of the Royal Society Interface
15 (2018).
date_created: 2019-01-20T22:59:19Z
date_published: 2018-12-12T00:00:00Z
date_updated: 2023-09-19T10:40:38Z
day: '12'
department:
- _id: EdHa
doi: 10.1098/rsif.2018.0395
external_id:
arxiv:
- '1612.01605'
isi:
- '000456783800002'
intvolume: ' 15'
isi: 1
issue: '149'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1612.01605
month: '12'
oa: 1
oa_version: Preprint
publication: Journal of the Royal Society Interface
publication_identifier:
issn:
- '17425689'
publication_status: published
publisher: Royal Society Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: Zipf's Law, unbounded complexity and open-ended evolution
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 15
year: '2018'
...
---
_id: '5961'
abstract:
- lang: eng
text: "The area of machine learning has made considerable progress over the past
decade, enabled by the widespread availability of large datasets, as well as by
improved algorithms and models. Given the large computational demands of machine
learning workloads, parallelism, implemented either through single-node concurrency
or through multi-node distribution, has been a third key ingredient to advances
in machine learning.\r\nThe goal of this tutorial is to provide the audience with
an overview of standard distribution techniques in machine learning, with an eye
towards the intriguing trade-offs between synchronization and communication costs
of distributed machine learning algorithms, on the one hand, and their convergence,
on the other.The tutorial will focus on parallelization strategies for the fundamental
stochastic gradient descent (SGD) algorithm, which is a key tool when training
machine learning models, from classical instances such as linear regression, to
state-of-the-art neural network architectures.\r\nThe tutorial will describe the
guarantees provided by this algorithm in the sequential case, and then move on
to cover both shared-memory and message-passing parallelization strategies, together
with the guarantees they provide, and corresponding trade-offs. The presentation
will conclude with a broad overview of ongoing research in distributed and concurrent
machine learning. The tutorial will assume no prior knowledge beyond familiarity
with basic concepts in algebra and analysis.\r\n"
article_processing_charge: No
author:
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Alistarh D-A. A brief tutorial on distributed and concurrent machine learning.
In: Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing
- PODC ’18. ACM Press; 2018:487-488. doi:10.1145/3212734.3212798'
apa: 'Alistarh, D.-A. (2018). A brief tutorial on distributed and concurrent machine
learning. In Proceedings of the 2018 ACM Symposium on Principles of Distributed
Computing - PODC ’18 (pp. 487–488). Egham, United Kingdom: ACM Press. https://doi.org/10.1145/3212734.3212798'
chicago: Alistarh, Dan-Adrian. “A Brief Tutorial on Distributed and Concurrent Machine
Learning.” In Proceedings of the 2018 ACM Symposium on Principles of Distributed
Computing - PODC ’18, 487–88. ACM Press, 2018. https://doi.org/10.1145/3212734.3212798.
ieee: D.-A. Alistarh, “A brief tutorial on distributed and concurrent machine learning,”
in Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing
- PODC ’18, Egham, United Kingdom, 2018, pp. 487–488.
ista: 'Alistarh D-A. 2018. A brief tutorial on distributed and concurrent machine
learning. Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing
- PODC ’18. PODC: Principles of Distributed Computing, 487–488.'
mla: Alistarh, Dan-Adrian. “A Brief Tutorial on Distributed and Concurrent Machine
Learning.” Proceedings of the 2018 ACM Symposium on Principles of Distributed
Computing - PODC ’18, ACM Press, 2018, pp. 487–88, doi:10.1145/3212734.3212798.
short: D.-A. Alistarh, in:, Proceedings of the 2018 ACM Symposium on Principles
of Distributed Computing - PODC ’18, ACM Press, 2018, pp. 487–488.
conference:
end_date: 2018-07-27
location: Egham, United Kingdom
name: 'PODC: Principles of Distributed Computing'
start_date: 2018-07-23
date_created: 2019-02-13T09:48:55Z
date_published: 2018-07-27T00:00:00Z
date_updated: 2023-09-19T10:42:28Z
day: '27'
department:
- _id: DaAl
doi: 10.1145/3212734.3212798
external_id:
isi:
- '000458186900063'
isi: 1
language:
- iso: eng
month: '07'
oa_version: None
page: 487-488
publication: Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing -
PODC '18
publication_identifier:
isbn:
- '9781450357951'
publication_status: published
publisher: ACM Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: A brief tutorial on distributed and concurrent machine learning
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2018'
...
---
_id: '5960'
abstract:
- lang: eng
text: In this paper we present a reliable method to verify the existence of loops
along the uncertain trajectory of a robot, based on proprioceptive measurements
only, within a bounded-error context. The loop closure detection is one of the
key points in simultaneous localization and mapping (SLAM) methods, especially
in homogeneous environments with difficult scenes recognitions. The proposed approach
is generic and could be coupled with conventional SLAM algorithms to reliably
reduce their computing burden, thus improving the localization and mapping processes
in the most challenging environments such as unexplored underwater extents. To
prove that a robot performed a loop whatever the uncertainties in its evolution,
we employ the notion of topological degree that originates in the field of differential
topology. We show that a verification tool based on the topological degree is
an optimal method for proving robot loops. This is demonstrated both on datasets
from real missions involving autonomous underwater vehicles and by a mathematical
discussion.
article_processing_charge: No
author:
- first_name: Simon
full_name: Rohou, Simon
last_name: Rohou
- first_name: Peter
full_name: Franek, Peter
id: 473294AE-F248-11E8-B48F-1D18A9856A87
last_name: Franek
orcid: 0000-0001-8878-8397
- first_name: Clément
full_name: Aubry, Clément
last_name: Aubry
- first_name: Luc
full_name: Jaulin, Luc
last_name: Jaulin
citation:
ama: Rohou S, Franek P, Aubry C, Jaulin L. Proving the existence of loops in robot
trajectories. The International Journal of Robotics Research. 2018;37(12):1500-1516.
doi:10.1177/0278364918808367
apa: Rohou, S., Franek, P., Aubry, C., & Jaulin, L. (2018). Proving the existence
of loops in robot trajectories. The International Journal of Robotics Research.
SAGE Publications. https://doi.org/10.1177/0278364918808367
chicago: Rohou, Simon, Peter Franek, Clément Aubry, and Luc Jaulin. “Proving the
Existence of Loops in Robot Trajectories.” The International Journal of Robotics
Research. SAGE Publications, 2018. https://doi.org/10.1177/0278364918808367.
ieee: S. Rohou, P. Franek, C. Aubry, and L. Jaulin, “Proving the existence of loops
in robot trajectories,” The International Journal of Robotics Research,
vol. 37, no. 12. SAGE Publications, pp. 1500–1516, 2018.
ista: Rohou S, Franek P, Aubry C, Jaulin L. 2018. Proving the existence of loops
in robot trajectories. The International Journal of Robotics Research. 37(12),
1500–1516.
mla: Rohou, Simon, et al. “Proving the Existence of Loops in Robot Trajectories.”
The International Journal of Robotics Research, vol. 37, no. 12, SAGE Publications,
2018, pp. 1500–16, doi:10.1177/0278364918808367.
short: S. Rohou, P. Franek, C. Aubry, L. Jaulin, The International Journal of Robotics
Research 37 (2018) 1500–1516.
date_created: 2019-02-13T09:36:20Z
date_published: 2018-10-24T00:00:00Z
date_updated: 2023-09-19T10:41:59Z
day: '24'
department:
- _id: UlWa
doi: 10.1177/0278364918808367
external_id:
arxiv:
- '1712.01341'
isi:
- '000456881100004'
intvolume: ' 37'
isi: 1
issue: '12'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1712.01341
month: '10'
oa: 1
oa_version: Preprint
page: 1500-1516
publication: The International Journal of Robotics Research
publication_identifier:
eissn:
- 1741-3176
issn:
- 0278-3649
publication_status: published
publisher: SAGE Publications
quality_controlled: '1'
scopus_import: '1'
status: public
title: Proving the existence of loops in robot trajectories
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 37
year: '2018'
...