An ADMM Based Framework for AutoML Pipeline Configuration

We study the AutoML problem of automatically configuring machine learning pipelines by jointly selecting algorithms and their appropriate hyper-parameters for all steps in supervised learning pipelines. This black-box (gradient-free) optimization with mixed integer & continuous variables is a challenging problem. We propose a novel AutoML scheme by leveraging the alternating direction method of multipliers (ADMM). The proposed framework is able to (i) decompose the optimization problem into easier sub-problems that have a reduced number of variables and circumvent the challenge of mixed variable categories, and (ii) incorporate black-box constraints along-side the black-box optimization objective. We empirically evaluate the flexibility (in utilizing existing AutoML techniques), effectiveness (against open source AutoML toolkits),and unique capability (of executing AutoML with practically motivated black-box constraints) of our proposed scheme on a collection of binary classification data sets from UCI ML& OpenML repositories. We observe that on an average our framework provides significant gains in comparison to other AutoML frameworks (Auto-sklearn & TPOT), highlighting the practical advantages of this framework

Dial 'B' for burnout? The experience of job burnout in a telephone call centre

Melbourne, VI

AN EVALUATION OF FACTORS AFFECTING THE CO2- C SINK STRENGTH OF AG-LIME ADDED TO TWO TRINIDAD ACID SOILS

The most recent Intergovernmental Panel on Climate Change (IPCC) greenhouse gas (GHG) inventory guidelines recognizes that CO2 is not always the end product of ag-lime dissolution in soils and now allows countries to report on their own emission factors once it is supported by sound research findings. This study was therefore established to assess the effects of additions of organic amendments (biochar and poultry litter) and ammonium N on the magnitude of the CO2 flux and the carbon sequestration potential of ag-lime when added to two diverse soils (a peaty clay and a sand). The soil treatments with the equivalent of 80g oven dry soil (ODS) were incubated in modified 500 mL mason jars. At each measurement, the alkali-trap attached to the cover was installed ensuring proper sealing of the jar opening and left for 24 hrs to absorb the CO2 emitted from the soil. Fluxes were measured at days 1, 3, 6, 9, 10, 15, 18, 21, 24, 28 and, 31, and all soil treatments were initially brought to 100% field capacity and rewetted three times thereafter. Analysis of the data showed that soil type, organic matter and ag-lime additions had a significant effect (P<0.05) on CO2 emissions. The effect of time was significant on the rates of CO2 emissions, showing a decline in the emission rate from an overall mean of 33.8 mg CO2/kgODS/hr at day 1 down to 1.98 mg CO2/kgODS/hr. The peaty clay fluxes were consistently higher than those from the sand, and soils treated with poultry litter were also statistically (P<0.05) consistently higher than those with biochar and no organic matter additions. Given that ag-lime addition to soil is known to have a priming effect on organic matter decomposition, evidence for carbon sequestration was seen with both soils; whereby the increase in CO2 emissions following the addition of ag-lime was much lower in the presence of poultry litter compared to soils with biochar and no organic matter addition

Organic Residues and Ammonium Effects on CO₂ Emissions and Soil Quality Indicators in Limed Acid Tropical Soils

Aglime (agricultural lime), commonly applied to acid soils to increase the soil pH and productivity, may lead to the release of CO2 into the atmosphere or to carbon (C) sequestration, although the processes involved are not fully understood. As large acreages of arable land are limed annually, exploring soil management practices that reduce aglime-induced CO2 emissions from acid soils while maintaining or improving the soil quality is paramount to mitigating the effects of global climate change. This study, therefore, assessed the effects of organic residues and ammonium on CO2 emissions and soil quality indicators in two limed soils. Two contrasting acid soils (Nariva series, Mollic Fluvaquents and Piarco series, Typic Kanhaplaquults) were amended with varying combinations of aglime (0% and 0.2% w/w CaCO3), organic residue (0% and 5% w/w biochar or poultry litter), and NH4-N (0% and 0.02% w/w) and were incubated in 300 mL glass jars for 31 days. The sampling for CO2 was performed on 11 occasions over the course of the incubation, while soil sampling was conducted at the end. The results indicate that aglime application significantly (p &lt; 0.05) increased the cumulative CO2 emissions in all cases except with the addition of poultry litter. Alternatively, ammonium did not regulate the effect of aglime on CO2 emissions, which was likely because of the low rate at which it was applied in comparison to aglime. The results also showed that poultry litter significantly (p &lt; 0.05) increased the soil electrical conductivity (EC), available nitrogen (N), and pH, especially in the Piarco soil, while the hardwood biochar had little to no effect on the soil properties. Our findings indicate the potential for utilizing poultry litter to reduce the impact of aglime on CO2 emissions while improving the soil quality. Further studies utilizing 13C to trace aglime CO2 emissions are, however, required to identify the mechanism(s) that contributed to this reduction in the emissions