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7289 Publications


2020 | Published | Journal Article | IST-REx-ID: 8077 | OA
Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence
Y. Shehu, O.S. Iyiola, Applied Numerical Mathematics 157 (2020) 315–337.
[Submitted Version] View | Files available | DOI | WoS
 

2020 | Published | Journal Article | IST-REx-ID: 6593 | OA
An efficient projection-type method for monotone variational inequalities in Hilbert spaces
Y. Shehu, X.-H. Li, Q.-L. Dong, Numerical Algorithms 84 (2020) 365–388.
[Submitted Version] View | Files available | DOI | WoS
 

2020 | Published | Conference Paper | IST-REx-ID: 8725 | OA
The splay-list: A distribution-adaptive concurrent skip-list
V. Aksenov, D.-A. Alistarh, A. Drozdova, A. Mohtashami, in:, 34th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020, p. 3:1-3:18.
[Published Version] View | Files available | DOI | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 8722 | OA
Taming unbalanced training workloads in deep learning with partial collective operations
S. Li, T.B.-N. Tal Ben-Nun, S.D. Girolamo, D.-A. Alistarh, T. Hoefler, in:, Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2020, pp. 45–61.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 7636 | OA
Non-blocking interpolation search trees with doubly-logarithmic running time
T.A. Brown, A. Prokopec, D.-A. Alistarh, in:, Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2020, pp. 276–291.
[Published Version] View | DOI | Download Published Version (ext.) | WoS
 

2020 | Published | Conference Paper | IST-REx-ID: 15086 | OA
Adaptive gradient quantization for data-parallel SGD
F. Faghri, I. Tabrizian, I. Markov, D.-A. Alistarh, D. Roy, A. Ramezani-Kebrya, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2020.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 9632 | OA
WoodFisher: Efficient second-order approximation for neural network compression
Singh, Sidak Pal, WoodFisher: Efficient second-order approximation for neural network compression. 33. 2020
[Published Version] View | Download Published Version (ext.) | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 9631 | OA
Scalable belief propagation via relaxed scheduling
Aksenov, Vitaly, Scalable belief propagation via relaxed scheduling. 33. 2020
[Published Version] View | Download Published Version (ext.) | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 8272 | OA
Stochastic games with lexicographic reachability-safety objectives
K. Chatterjee, J.P. Katoen, M. Weininger, T. Winkler, in:, International Conference on Computer Aided Verification, Springer Nature, 2020, pp. 398–420.
[Published Version] View | Files available | DOI | WoS | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 7955 | OA
Approximating values of generalized-reachability stochastic games
Ashok, Pranav, Approximating values of generalized-reachability stochastic games. Proceedings of the 35th Annual ACM/IEEE Symposium on Logic in Computer Science . 2020
[Published Version] View | Files available | DOI | WoS | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 10673 | OA
A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits
R. Hasani, M. Lechner, A. Amini, D. Rus, R. Grosu, in:, Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 4082–4093.
[Published Version] View | Files available | Download Published Version (ext.)
 

2020 | Published | Conference Paper | IST-REx-ID: 10672 | OA
Learning representations for binary-classification without backpropagation
M. Lechner, in:, 8th International Conference on Learning Representations, ICLR, 2020.
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2020 | Published | Conference Paper | IST-REx-ID: 8623 | OA
Monitorability under assumptions
T.A. Henzinger, N.E. Sarac, in:, Runtime Verification, Springer Nature, 2020, pp. 3–18.
[Submitted Version] View | Files available | DOI | WoS
 

2020 | Published | Conference Paper | IST-REx-ID: 9103 | OA
Lagrangian reachtubes: The next generation
S. Gruenbacher, J. Cyranka, M. Lechner, M.A. Islam, S.A. Smolka, R. Grosu, in:, Proceedings of the 59th IEEE Conference on Decision and Control, IEEE, 2020, pp. 1556–1563.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 9202 | OA
Hybridization for stability verification of nonlinear switched systems
M. Garcia Soto, P. Prabhakar, in:, 2020 IEEE Real-Time Systems Symposium, IEEE, 2020, pp. 244–256.
[Submitted Version] View | Files available | DOI | WoS
 

2020 | Published | Journal Article | IST-REx-ID: 8679
Neural circuit policies enabling auditable autonomy
M. Lechner, R. Hasani, A. Amini, T.A. Henzinger, D. Rus, R. Grosu, Nature Machine Intelligence 2 (2020) 642–652.
View | Files available | DOI | WoS
 

2020 | Published | Conference Paper | IST-REx-ID: 8012 | OA
Inductive sequentialization of asynchronous programs
B. Kragl, C. Enea, T.A. Henzinger, S.O. Mutluergil, S. Qadeer, in:, Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation, Association for Computing Machinery, 2020, pp. 227–242.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | WoS
 

2020 | Published | Conference Paper | IST-REx-ID: 8195 | OA
Refinement for structured concurrent programs
B. Kragl, S. Qadeer, T.A. Henzinger, in:, Computer Aided Verification, Springer Nature, 2020, pp. 275–298.
[Published Version] View | Files available | DOI | WoS
 

2020 | Published | Conference Paper | IST-REx-ID: 8194 | OA
An SMT theory of fixed-point arithmetic
M. Baranowski, S. He, M. Lechner, T.S. Nguyen, Z. Rakamarić, in:, Automated Reasoning, Springer Nature, 2020, pp. 13–31.
[Published Version] View | DOI | Download Published Version (ext.) | WoS
 

2020 | Published | Conference Paper | IST-REx-ID: 8704 | OA
Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme
Lechner, Mathias, Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme. Proceedings - IEEE International Conference on Robotics and Automation. 2020
[Submitted Version] View | Files available | DOI | WoS
 

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