Better predictions when models are wrong or underspecified

Many statistical methods rely on models of reality in order to learn from data and to make predictions about future data. By necessity, these models usually do not match reality exactly, but are either wrong (none of the hypotheses in the model provides an accurate description of reality) or underspecified (the hypotheses in the model describe only part of the data). In this thesis, we discuss three scenarios involving models that are wrong or underspecified. In each case, we find that standard statistical methods may fail, sometimes dramatically, and present different methods that continue to perform well even if the models are wrong or underspecified. The first two of these scenarios involve regression problems and investigate AIC (Akaike's Information Criterion) and Bayesian statistics. The third scenario has the famous Monty Hall problem as a special case, and considers the question how we can update our belief about an unknown outcome given new evidence when the precise relation between outcome and evidence is unknown.UBL - phd migration 201

An Investigation Into the Changes of Loudness Perception in Relation to Changes in Crest Factor for Octave Bands

Even though modern technology has the capability to make audio sound better than it ever has, there is still an ongoing argument about the compression levels with music. Heavy compression has been found in previous studies to be detrimental to quality but before a full understanding into how compression affects audio, a fundamental knowledge of the affects across different frequencies is important. Using pink noise in a series of tests to determine the level of compression and how it changes the perceived loudness across different frequency bands and across different amplitude characteristics gave an insight into how compression affects complex audio. It was found that lower octaves behaved differently to the expected outcome where it was found to be perceived as louder despite no extra treatment from other frequency bands. It was however also found that all frequency bands increased in loudness as a result of compression

Minimum Description Length Penalization for Group and Multi-Task Sparse Learning

We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an elegant way of incorporating arbitrary sparsity patterns in the feature space by using two-part MDL coding schemes. We present MIC based models for the problems of grouped feature selection (MIC-GROUP) and multi-task feature selection (MIC-MULTI). MIC-GROUP assumes that the features are divided into groups and induces two level sparsity, selecting a subset of the feature groups, and also selecting features within each selected group. MIC-MULTI applies when there are multiple related tasks that share the same set of potentially predictive features. It also induces two level sparsity, selecting a subset of the features, and then selecting which of the tasks each feature should be added to. Lastly, we propose a model, TRANSFEAT, that can be used to transfer knowledge from a set of previously learned tasks to a new task that is expected to share similar features. All three methods are designed for selecting a small set of predictive features from a large pool of candidate features. We demonstrate the effectiveness of our approach with experimental results on data from genomics and from word sense disambiguation problems

Compression-based inference of network motif sets

Physical and functional constraints on biological networks lead to complex topological patterns across multiple scales in their organization. A particular type of higher-order network feature that has received considerable interest is network motifs, defined as statistically regular subgraphs. These may implement fundamental logical and computational circuits and are referred as ``building blocks of complex networks''. Their well-defined structures and small sizes also enables the testing of their functions in synthetic and natural biological experiments. The statistical inference of network motifs is however fraught with difficulties, from defining and sampling the right null model to accounting for the large number of possible motifs and their potential correlations in statistical testing. Here we develop a framework for motif mining based on lossless network compression using subgraph contractions. The minimum description length principle allows us to select the most significant set of motifs as well as other prominent network features in terms of their combined compression of the network. The approach inherently accounts for multiple testing and correlations between subgraphs and does not rely on a priori specification of an appropriate null model. This provides an alternative definition of motif significance which guarantees more robust statistical inference. Our approach overcomes the common problems in classic testing-based motif analysis. We apply our methodology to perform comparative connectomics by evaluating the compressibility and the circuit motifs of a range of synaptic-resolution neural connectomes

Project Report: 'still every year they went'

‘still every year they went’ involves the rewriting of songs from the UK fisheries and the recording of these arrangements at sea in a working fishing boat (the boat and its own sounds being of particular importance during this process). Subsequent captured performances and field recordings will then be re-composed for surround sound, outputting both a fixed album of music (due for release on Armellodie Records), but also developing into a live performance event in surround touring in August of this year, starting at the Tate St Ives. The proposed paper speaks explicitly to the conference themes of innovative music creation and music production. We will explicate the motives and methods of this current practice based research project which engages in a collision of fidelities, technology and compositional practices belonging to; on the one hand traditional folksong, and on the other to sound-based music. Both researchers have a strong background in the application of field recording within composition and music that is located geographically. This paper will discuss both the technical and compositional innovations of the project with some specific focus on the ‘ontological catastrophe’ of recording (drawing from Lamb’s research into recording as a form of taxidermy) and the inevitable failure of ‘immersive’ audio, particularly in the challenging environment of the ocean and the migrations of maritime working song from sea to land to sea, and back to land again, particularly given the contemporary vessel’s lack of need to working songs. As such, we make an investigation of the status and performance/production of folksong through technological innovation within the contexts of site and composition for maritime song

Better predictions when models are wrong or underspecified

Many statistical methods rely on models of reality in order to learn from data and to make predictions about future data. By necessity, these models usually do not match reality exactly, but are either wrong (none of the hypotheses in the model provides an accurate description of reality) or underspecified (the hypotheses in the model describe only part of the data). In this thesis, we discuss three scenarios involving models that are wrong or underspecified. In each case, we find that standard statistical methods may fail, sometimes dramatically, and present different methods that continue to perform well even if the models are wrong or underspecified. The first two of these scenarios involve regression problems and investigate AIC (Akaike's Information Criterion) and Bayesian statistics. The third scenario has the famous Monty Hall problem as a special case, and considers the question how we can update our belief about an unknown outcome given new evidence when the precise relation between outcome and evidence is unknown.UBL - phd migration 201

Management of Patellar Chondral Defects with Autologous Matrix Induced Chondrogenesis (AMIC) Compared to Microfractures: A Four Years Follow-Up Clinical Trial.

INTRODUCTION: Evidence on the management of chondral defects of the patella arises from studies in which the patellofemoral joint was treated together with the femorotibial joint and primary and revision settings. Furthermore, the superiority of Autologous Matrix Induced Chondrogenesis (AMIC) over microfractures (MFx) for patellar chondral defects is uncertain. Therefore, the present study compared primary isolated AMIC versus MFx for focal unipolar chondral defects of the patellar facet joints at midterm follow-up. METHODS: Patients undergoing AMIC or isolated MFx surgery for borderline-sized focal unipolar chondral defects of the patellar facet joints were followed at our institution. All surgeries were performed in the same fashion by experienced surgeons. A parapatellar arthrotomy was adopted in all surgeries. The outcomes of interest were: Visual Analogic Scale (VAS), Tegner Activity Scale, International Knee Documentation Committee (IKDC), and the Lysholm scores. The Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) was assessed by a blinded radiologist, who had not been involved in the clinical management of the patients. RESULTS: 38 patients were enrolled in the present study: 27 underwent AMIC, and 11 MFx. The mean follow-up was 45.1 months. The mean age of the patients at baseline was 34.5 years. The mean size of the defect was 2.6 cm2. The MFx cohort experienced a shorter length of the hospitalization (P = 0.008). There was no difference in terms of follow-up and previous symptoms duration, mean age, sex, side, defect size, and BMI. At last follow-up, the AMIC cohort reported greater IKDC (P = 0.01), Lysholm (P = 0.009), and Tegner (P = 0.02), along with a low rate of failure (P = 0.02). VAS was lower in the AMIC group (P = 0.002). No difference was found in the MOCART score (P = 0.09), rates of revision (P = 0.06), and arthroplasty (P = 0.2). CONCLUSION: The AMIC procedure achieves greater IKDC and Lysholm score, and a significant reduction of the VAS score in the management of patellar chondral defects. The Tegner scale demonstrated greater activity after AMIC procedure. Finally, the AMIC group evidenced a lower rate of failure. Similarity was found on MOCART score, rates of revision, and arthroplasty between the two procedures

Management of Patellar Chondral Defects with Autologous Matrix Induced Chondrogenesis (AMIC) Compared to Microfractures: A Four Years Follow-Up Clinical Trial.

INTRODUCTION: Evidence on the management of chondral defects of the patella arises from studies in which the patellofemoral joint was treated together with the femorotibial joint and primary and revision settings. Furthermore, the superiority of Autologous Matrix Induced Chondrogenesis (AMIC) over microfractures (MFx) for patellar chondral defects is uncertain. Therefore, the present study compared primary isolated AMIC versus MFx for focal unipolar chondral defects of the patellar facet joints at midterm follow-up. METHODS: Patients undergoing AMIC or isolated MFx surgery for borderline-sized focal unipolar chondral defects of the patellar facet joints were followed at our institution. All surgeries were performed in the same fashion by experienced surgeons. A parapatellar arthrotomy was adopted in all surgeries. The outcomes of interest were: Visual Analogic Scale (VAS), Tegner Activity Scale, International Knee Documentation Committee (IKDC), and the Lysholm scores. The Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) was assessed by a blinded radiologist, who had not been involved in the clinical management of the patients. RESULTS: 38 patients were enrolled in the present study: 27 underwent AMIC, and 11 MFx. The mean follow-up was 45.1 months. The mean age of the patients at baseline was 34.5 years. The mean size of the defect was 2.6 cm2. The MFx cohort experienced a shorter length of the hospitalization (P = 0.008). There was no difference in terms of follow-up and previous symptoms duration, mean age, sex, side, defect size, and BMI. At last follow-up, the AMIC cohort reported greater IKDC (P = 0.01), Lysholm (P = 0.009), and Tegner (P = 0.02), along with a low rate of failure (P = 0.02). VAS was lower in the AMIC group (P = 0.002). No difference was found in the MOCART score (P = 0.09), rates of revision (P = 0.06), and arthroplasty (P = 0.2). CONCLUSION: The AMIC procedure achieves greater IKDC and Lysholm score, and a significant reduction of the VAS score in the management of patellar chondral defects. The Tegner scale demonstrated greater activity after AMIC procedure. Finally, the AMIC group evidenced a lower rate of failure. Similarity was found on MOCART score, rates of revision, and arthroplasty between the two procedures

Lateral retinaculum: past and present

Povećana napetost lateralnog retinakula patele može se javiti kao samostalni entitet ili u sklopu drugih poremećaja patelofemoralnog zgloba kao što su patelofemoralna displazija, lateralna nestabilnost patele, ozljede medijalnog patelofemoralnog ligamenta i hondromalacija. Presijecanje lateralnog retinakula, kako bi se postigao bolji balans aktivnih i pasivnih stabilizatora patele i na taj način korigirao njen položaj, bila je jedna od najizvođenijih operacija u ortopediji bez obzira na etiologiju poremećaja. Biomehaničke i kliničke analize pokazale su mogućnost nastanka brojnih komplikacija koje mogu nastati neselektivnom primjenom ove operacijske tehnike od kojih je najteža medijalna nestabilnost patele. Danas se kao metoda za korigiranje napetosti lateralnih stabilizatora patele češće upotrebljava tehnika produljivanja lateralnog retinakula kojom se puno bolje može regulirati napetost lateralnih struktura uz značajno manje komplikacija.Tightness of the lateral patellar soft tissue complex could be isolated entity or associated with other patellofemoral disorders such as patellofemoral dysplasia, lateral patella instability, medial patellofemoral ligament injury and chondromalatia. Lateral retinacular release was a method of choice among orthopaedic surgeons for improving the patellofemoral balance and congruency regardless the etiology of patellofemoral disorders. Biomechanical and clinical studies have shown that nonselective use of this surgical method could cause numerous complications among which medial patellar instability is the worst. Today most orthopaedic surgeons prefer lengthening instead release, because lateral lengthening is a more precise technique, with reduced complication rates