| 1. |
- Forssen, Christian, 1974, et al.
(författare)
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The Ab Initio No-core Shell Model
- 2009
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Ingår i: Few-Body Systems. - : Springer Science and Business Media LLC. - 1432-5411 .- 0177-7963. ; 45:2, s. 111-
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Konferensbidrag (refereegranskat)abstract
- This contribution reviews a number of applications of the ab initio no-core shell model (NCSM) within nuclear physics and beyond. We will highlight a nuclear-structure study of the A = 12 isobar using a chiral NN + 3NF interaction. In the spirit of this workshop we will also mention the new development of the NCSM formalism to describe open channels and to approach the problem of nuclear reactions. Finally, we will illustrate the universality of the many-body problem by presenting the recent adaptation of the NCSM effective-interaction approach to study the many-boson problem in an external trapping potential with short-range interactions.This article is based on the presentation by C. Forssén at the Fifth Workshop on Critical Stability, Erice, Sicily.
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| 2. |
- Olsson, Carl, 1978, et al.
(författare)
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Relaxations for Non-Separable Cardinality/Rank Penalties
- 2021
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Ingår i: Proceedings of the IEEE International Conference on Computer Vision. - 1550-5499. ; 2021-October, s. 162-171
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Konferensbidrag (refereegranskat)abstract
- Rank and cardinality penalties are hard to handle in optimization frameworks due to non-convexity and discontinuity. Strong approximations have been a subject of intense study and numerous formulations have been proposed. Most of these can be described as separable, meaning that they apply a penalty to each element (or singular value) based on size, without considering the joint distribution. In this paper we present a class of non-separable penalties and give a recipe for computing strong relaxations suitable for optimization. In our analysis of this formulation we first give conditions that ensure that the global ly optimal solution of the relaxation is the same as that of the original (unrelaxed) objective. We then show how a stationary point can be guaranteed to be unique under the restricted isometry property (RIP) assumption.1
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| 3. |
- Wiqvist, Samuel, et al.
(författare)
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Partially Exchangeable Networks and architectures for learning summary statistics in Approximate Bayesian Computation
- 2019
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Ingår i: Proceedings of the 36th International Conference on Machine Learning. - : PMLR. ; 2019-June, s. 11795-11804
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Konferensbidrag (refereegranskat)abstract
- We present a novel family of deep neural architectures, named partially exchangeable networks (PENs) that leverage probabilistic symmetries. By design, PENs are invariant to block-switch transformations, which characterize the partial exchangeability properties of conditionally Markovian processes. Moreover, we show that any block-switch invariant function has a PEN-like representation. The DeepSets architecture is a special case of PEN and we can therefore also target fully exchangeable data. We employ PENs to learn summary statistics in approximate Bayesian computation (ABC). When comparing PENs to previous deep learning methods for learning summary statistics, our results are highly competitive, both considering time series and static models. Indeed, PENs provide more reliable posterior samples even when using less training data.
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| 4. |
- Örnhag, Marcus Valtonen, et al.
(författare)
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Differentiable Fixed-Rank Regularisation using Bilinear Parameterization
- 2020
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Ingår i: 30th British Machine Vision Conference 2019, BMVC 2019.
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Konferensbidrag (refereegranskat)abstract
- Low rank structures are present in many applications of computer vision and machine learning. A popular approach consists of explicitly parameterising the set or matrices with sought rank, leading to a bilinear factorisation, reducing the problem to find the bilinear factors. While such an approach can be efficiently implemented using secondorder methods, such as Levenberg–Marquardt (LM) or Variable Projection (VarPro), it suffers from the presence of local minima, which makes theoretical optimality guarantees hard to derive. Another approach is to penalise non-zero singular values to enforce a low-rank structure. In certain cases, global optimality guarantees are known; however, such methods often lead to non-differentiable (and even discontinuous) objectives, for which it is necessary to use subgradient methods and splitting schemes. If the objective is complex, such as in structure from motion, the convergence rates for such methods can be very slow. In this paper we show how optimality guarantees can be lifted to methods that employ bilinear parameterisation when the sought rank is known. Using this approach the best of two worlds are combined: optimality guarantees and superior convergence speeds. We compare the proposed method to state-of-the-art solvers for prior-free non-rigid structure from motion.
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| 5. |
- Bylow, Erik, et al.
(författare)
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Minimizing the maximal rank
- 2016
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Ingår i: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. - 1063-6919. - 9781467388511 ; 2016-January, s. 5887-5895
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Konferensbidrag (refereegranskat)abstract
- In computer vision, many problems can be formulated as finding a low rank approximation of a given matrix. Ideally, if all elements of the measurement matrix are available, this is easily solved in the L2-norm using factorization. However, in practice this is rarely the case. Lately, this problem has been addressed using different approaches, one is to replace the rank term by the convex nuclear norm, another is to derive the convex envelope of the rank term plus a data term. In the latter case, matrices are divided into sub-matrices and the envelope is computed for each subblock individually. In this paper a new convex envelope is derived which takes all sub-matrices into account simultaneously. This leads to a simpler formulation, using only one parameter to control the trade-of between rank and data fit, for applications where one seeks low rank approximations of multiple matrices with the same rank. We show in this paper how our general framework can be used for manifold denoising of several images at once, as well as just denoising one image. Experimental comparisons show that our method achieves results similar to state-of-the-art approaches while being applicable for other problems such as linear shape model estimation.
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| 6. |
- Alizadehheidari, Mohammadreza, 1987, et al.
(författare)
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Nanoconfined circular DNA
- 2014
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Ingår i: 18th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2014. - 9780979806476 ; , s. 1353-1355
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Konferensbidrag (refereegranskat)abstract
- Studies of nanoconfined circular DNA are of interest both from a biological as well as a fundamental polymer physics perspective. We here present the use of nanofluidic channels as a tool for comparing statics and dynamics of the linear and circular configuration of the same DNA molecule.
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| 7. |
- Olsson, Carl, 1978, et al.
(författare)
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Non-convex Rank/Sparsity Regularization and Local Minima
- 2017
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Ingår i: Proceedings of the IEEE International Conference on Computer Vision. - 1550-5499. - 9781538610329 ; 2017-October, s. 332-340
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Konferensbidrag (refereegranskat)abstract
- This paper considers the problem of recovering either a low rank matrix or a sparse vector from observations of linear combinations of the vector or matrix elements. Recent methods replace the non-convex regularization with ℓ1 or nuclear norm relaxations. It is well known that this approach recovers near optimal solutions if a so called restricted isometry property (RIP) holds. On the other hand it also has a shrinking bias which can degrade the solution. In this paper we study an alternative non-convex regularization term that does not suffer from this bias. Our main theoretical results show that if a RIP holds then the stationary points are often well separated, in the sense that their differences must be of high cardinality/rank. Thus, with a suitable initial solution the approach is unlikely to fall into a bad local minimum. Our numerical tests show that the approach is likely to converge to a better solution than standard ℓ1/nuclear-norm relaxation even when starting from trivial initializations. In many cases our results can also be used to verify global optimality of our method.
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| 8. |
- Örnhag, Marcus Valtonen, et al.
(författare)
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Bilinear Parameterization for Non-Separable Singular Value Penalties
- 2021
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Ingår i: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. - 1063-6919. ; , s. 3896-3905
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Konferensbidrag (refereegranskat)abstract
- Low rank inducing penalties have been proven to successfully uncover fundamental structures considered in computer vision and machine learning; however, such methods generally lead to non-convex optimization problems. Since the resulting objective is non-convex one often resorts to using standard splitting schemes such as Alternating Direction Methods of Multipliers (ADMM), or other subgradient methods, which exhibit slow convergence in the neighbourhood of a local minimum. We propose a method using second order methods, in particular the variable projection method (VarPro), by replacing the nonconvex penalties with a surrogate capable of converting the original objectives to differentiable equivalents. In this way we benefit from faster convergence.The bilinear framework is compatible with a large family of regularizers, and we demonstrate the benefits of our approach on real datasets for rigid and non-rigid structure from motion. The qualitative difference in reconstructions show that many popular non-convex objectives enjoy an advantage in transitioning to the proposed framework.
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| 9. |
- Altstadt, S.G., et al.
(författare)
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B-13,B-14(n,gamma) via Coulomb Dissociation for Nucleosynthesis towards the r-Process
- 2014
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Ingår i: Nuclear Data Sheets. - : Elsevier BV. - 1095-9904 .- 0090-3752. ; 120, s. 197-200
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Konferensbidrag (refereegranskat)abstract
- Radioactive beams of 14,15B produced by fragmentation of a primary 40Ar beam were directed onto a Pb target to investigate the neutron breakup within the Coulomb field. The experiment was performed at the LAND/R3B setup. Preliminary results for the Coulomb dissociation cross sections as well as for the astrophysically interesting inverse reactions, 13,14B(n,γ), are presented.
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| 10. |
- Berntsson Svensson, Richard, et al.
(författare)
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Prioritization of quality requirements : State of practice in eleven companies
- 2011
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Ingår i: 2011 IEEE 19th International Requirements Engineering Conference, RE 2011; Trento; 29 August 2011 through 2 September 2011. - Trento : IEEE. - 9781457709234 ; , s. 69-78, s. 69-78
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Konferensbidrag (refereegranskat)abstract
- Requirements prioritization is recognized as an important but challenging activity in software product development. For a product to be successful, it is crucial to find the right balance among competing quality requirements. Although literature offers many methods for requirements prioritization, the research on prioritization of quality requirements is limited. This study identifies how quality requirements are prioritized in practice at 11 successful companies developing software intensive systems. We found that ad-hoc prioritization and priority grouping of requirements are the dominant methods for prioritizing quality requirements. The results also show that it is common to use customer input as criteria for prioritization but absence of any criteria was also common. The results suggests that quality requirements by default have a lower priority than functional requirements, and that they only get attention in the prioritizing process if decision-makers are dedicated to invest specific time and resources on QR prioritization. The results of this study may help future research on quality requirements to focus investigations on industry-relevant issues.
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