MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-wise Pruning Error Metric

Vision-language pre-trained models have achieved impressive performance on various downstream tasks. However, their large model sizes hinder their utilization on platforms with limited computational resources. We find that directly using smaller pre-trained models and applying magnitude-based pruning on CLIP models leads to inflexibility and inferior performance. Recent efforts for VLP compression either adopt uni-modal compression metrics resulting in limited performance or involve costly mask-search processes with learnable masks. In this paper, we first propose the Module-wise Pruning Error (MoPE) metric, accurately assessing CLIP module importance by performance decline on cross-modal tasks. Using the MoPE metric, we introduce a unified pruning framework applicable to both pre-training and task-specific fine-tuning compression stages. For pre-training, MoPE-CLIP effectively leverages knowledge from the teacher model, significantly reducing pre-training costs while maintaining strong zero-shot capabilities. For fine-tuning, consecutive pruning from width to depth yields highly competitive task-specific models. Extensive experiments in two stages demonstrate the effectiveness of the MoPE metric, and MoPE-CLIP outperforms previous state-of-the-art VLP compression methods.Comment: 18 pages, 8 figures, Published in CVPR202

The Methylococcus capsulatus (Bath) Secreted Protein, MopE*, Binds Both Reduced and Oxidized Copper

Under copper limiting growth conditions the methanotrophic bacterium Methylococcus capsulatus (Bath) secrets essentially only one protein, MopE*, to the medium. MopE* is a copper-binding protein whose structure has been determined by X-ray crystallography. The structure of MopE* revealed a unique high affinity copper binding site consisting of two histidine imidazoles and one kynurenine, the latter an oxidation product of Trp130. In this study, we demonstrate that the copper ion coordinated by this strong binding site is in the Cu(I) state when MopE* is isolated from the growth medium of M. capsulatus. The conclusion is based on X-ray Near Edge Absorption spectroscopy (XANES), and Electron Paramagnetic Resonance (EPR) studies. EPR analyses demonstrated that MopE*, in addition to the strong copper-binding site, also binds Cu(II) at two weaker binding sites. Both Cu(II) binding sites have properties typical of non-blue type II Cu (II) centres, and the strongest of the two Cu(II) sites is characterised by a relative high hyperfine coupling of copper (

A Scalable Framework to Choose Sellers in E-Marketplaces Using POMDPs

In multiagent e-marketplaces, buying agents need to select good sellers by querying other buyers (called advisors). Partially Observable Markov Decision Processes (POMDPs) have shown to be an effective framework for optimally selecting sellers by selectively querying advisors. However, current solution methods do not scale to hundreds or even tens of agents operating in the e-market. In this paper, we propose the Mixture of POMDP Experts (MOPE) technique, which exploits the inherent structure of trust-based domains, such as the seller selection problem in e-markets, by aggregating the solutions of smaller sub-POMDPs. We propose a number of variants of the MOPE approach that we analyze theoretically and empirically. Experiments show that MOPE can scale up to a hundred agents thereby leveraging the presence of more advisors to significantly improve buyer satisfaction

Exploring obesogenic environments : the design and development of the migrant obesogenic perception of the environment questionnaire (MOPE-Q) using a sample of Iranian migrants in Australia

BACKGROUND: Although there are a number of studies examining the effect of migration on obesity, these studies tend to focus on the role of acculturation in this relationship. However, there are indications that the change in environment may also be an important factor. Indeed, there is a considerable lack of psychometric tools designed to assess the association between environment and migrant health behaviour. The current study aimed to assess the literature on the link between environment and health for migrants, and on the basis of this information, design and develop the Migrant Obesogenic Perception of the Environment questionnaire (MOPE-Q). The MOPE-Q is the first comprehensive measure of the impact of environmental factors on migrant health behaviour related to physical activity, food habits and body image concern, as well as weight change. METHODS: Using a systematic approach, an initial pool of items for the questionnaire was developed and refined on the basis of rigorous content and face validity assessments and factor analysis. Further, reliability tests and test re-test studies were undertaken. Differences between Iranian and Australian environmental factors as they relate to obesogenic behaviour were explored using the developed measure. RESULTS: A total of 36 items were developed for the MOPE-Q. Principal factor analysis identified three similar factor structures of environmental factors related to obesity (categorized in terms of facilitators, barriers and pressures) for each country. The final questionnaire consisted of four distinct subscales pertaining specifically to the Australian environment and five subscales pertaining to the Iranian environment, accounting for 59% and 63%, respectively, of the total variance in obesity rates. Data suggests that the MOPE-Q is a reliable and valid self-report measure for assessing the relationship between environmental factors linked to obesity and obesogenic behaviour for this particular migrant group. CONCLUSION: The variations in environmental factors linked to obesity behaviour between home (Iran) and host (Australia) countries have been incorporated into the MOPE-Q instrument which has shown good psychometric properties. The MOPE-Q can be adapted and applied to other environments and populations to help explain changes in diet, physical activity patterns and body weight in migrant groups as they acculturate

Mother-Tongue Education Policy: Effects on Children’s Achievement in Reading Skills

Researches have shown that instructions received in the mother tongue are easily assimilated and permanent than those received in a second or foreign language. The thrust of this paper is to investigate on the effect of the mother tongue education policy on Nigeria children’s achievement in reading skills. The study adopted the randomized pre-test experimental and control group as design. Three research questions were used as a guide to the study. Two hypotheses were also raised for the study at 0.05 level of significance. The sample consisted of 215 primary 3 pupils taken from 4 primary schools in two geo-political zones. The sample size consisted of 110 pupils from rural and 105 pupils from urban schools. Standard deviation, means and analyses of covariance were used to analyze the data. The results indicates that children in the rural schools taught in the mother-tongue performed better than those from urban schools who were taught in English Language in reading skills. From the findings, it is recommended that the language policy on mother tongue usage should be enforced as medium of instruction in the early primary schools years. Keywords: Mother-tongue, policy, achievement and reading skills

Scaling POMDPs For Selecting Sellers in E-markets-Extended Version

In multiagent e-marketplaces, buying agents need to select good sellers by querying other buyers (called advisors). Partially Observable Markov Decision Processes (POMDPs) have shown to be an effective framework for optimally selecting sellers by selectively querying advisors. However, current solution methods do not scale to hundreds or even tens of agents operating in the e-market. In this paper, we propose the Mixture of POMDP Experts (MOPE) technique, which exploits the inherent structure of trust-based domains, such as the seller selection problem in e-markets, by aggregating the solutions of smaller sub-POMDPs. We propose a number of variants of the MOPE approach that we analyze theoretically and empirically. Experiments show that MOPE can scale up to a hundred agents thereby leveraging the presence of more advisors to significantly improve buyer satisfaction

Self-avoiding Tethered Membranes at the Tricritical Point

The scaling properties of self-avoiding tethered membranes at the tricritical point (theta-point) are studied by perturbative renormalization group methods. To treat the 3-body repulsive interaction (known to be relevant for polymers), new analytical and numerical tools are developped and applied to 1-loop calculations. These technics are a prerequisite to higher order calculations for self-avoiding membranes. The cross-over between the 3-body interaction and the modified 2-body interaction, attractive at long range, is studied through a new double epsilon-expansion. It is shown that the latter interaction is relevant for 2-dimensional membranes at the theta-point.Comment: 57 pages, gz-compressed ps-fil

Renormalization and Hyperscaling for Self-Avoiding Manifold Models

The renormalizability of the self-avoiding manifold (SAM) Edwards model is established. We use a new short distance multilocal operator product expansion (MOPE), which extends methods of local field theories to a large class of models with non-local singular interactions. This validates the direct renormalization method introduced before, as well as scaling laws. A new general hyperscaling relation for the configuration exponent gamma is derived. Manifolds at the Theta-point, and long range Coulomb interactions are briefly discussed.Comment: 10 pages + 1 figure, TeX + harvmac & epsf (uuencoded file), SPhT/93-07

POPE: Partial Order Preserving Encoding

Recently there has been much interest in performing search queries over encrypted data to enable functionality while protecting sensitive data. One particularly efficient mechanism for executing such queries is order-preserving encryption/encoding (OPE) which results in ciphertexts that preserve the relative order of the underlying plaintexts thus allowing range and comparison queries to be performed directly on ciphertexts. In this paper, we propose an alternative approach to range queries over encrypted data that is optimized to support insert-heavy workloads as are common in "big data" applications while still maintaining search functionality and achieving stronger security. Specifically, we propose a new primitive called partial order preserving encoding (POPE) that achieves ideal OPE security with frequency hiding and also leaves a sizable fraction of the data pairwise incomparable. Using only O(1) persistent and $O(n^\epsilon)$ non-persistent client storage for $0<\epsilon<1$, our POPE scheme provides extremely fast batch insertion consisting of a single round, and efficient search with O(1) amortized cost for up to $O(n^{1-\epsilon})$ search queries. This improved security and performance makes our scheme better suited for today's insert-heavy databases.Comment: Appears in ACM CCS 2016 Proceeding