title: Leveraging bagging for evolving data streams

authors: Bifet, Albert

subjects: computer science

abstract: Bagging, boosting and Random Forests are classical ensemble methods used to improve the performance of single classifiers. They obtain superior performance by increasing the accuracy and diversity of the single classifiers. Attempts have been made to reproduce these methods in the more challenging context of evolving data streams. In this paper, we propose a new variant of bagging, called leveraging bagging. This method combines the simplicity of bagging with adding more randomization to the input, and output of the classifiers. We test our method by performing an evaluation study on synthetic and real-world datasets comprising up to ten million examples.

text: Leveraging bagging for evolving data streams Bagging, boosting and Random Forests are classical ensemble methods used to improve the performance of single classifiers. They obtain superior performance by increasing the accuracy and diversity of the single classifiers. Attempts have been made to reproduce these methods in the more challenging context of evolving data streams. In this paper, we propose a new variant of bagging, called leveraging bagging. This method combines the simplicity of bagging with adding more randomization to the input, and output of the classifiers. We test our method by performing an evaluation study on synthetic and real-world datasets comprising up to ten million examples.

year: 2010

title: Progger 3: A low-overhead, tamper-proof provenance system

authors: Corrick, Tristan James Carlile

subjects: Progger

abstract: Data provenance, which describes how data is accessed and used since the time it is created, is a valuable resource with a wide range of uses. It can be used simply to know who has accessed one's data, or be used in more complex scenarios such as detecting malware. One method for collecting data provenance is to observe system calls. This thesis presents Progger 3, a system that observes system calls on Linux in order to collect data provenance. There are several existing provenance systems that observe system calls, but they have limitations regarding security, efficiency, and usability. Progger 3 remedies many of these limitations. As a result, Progger 3 is a working implementation of a provenance system that can observe any system call, guarantee tamper-proof provenance collection as long as the kernel on the client is not compromised, and transfer the provenance to other systems with confidentiality and integrity, all with a relatively low performance overhead.

text: Progger 3: A low-overhead, tamper-proof provenance system Data provenance, which describes how data is accessed and used since the time it is created, is a valuable resource with a wide range of uses. It can be used simply to know who has accessed one's data, or be used in more complex scenarios such as detecting malware. One method for collecting data provenance is to observe system calls. This thesis presents Progger 3, a system that observes system calls on Linux in order to collect data provenance. There are several existing provenance systems that observe system calls, but they have limitations regarding security, efficiency, and usability. Progger 3 remedies many of these limitations. As a result, Progger 3 is a working implementation of a provenance system that can observe any system call, guarantee tamper-proof provenance collection as long as the kernel on the client is not compromised, and transfer the provenance to other systems with confidentiality and integrity, all with a relatively low performance overhead.

year: 2021

title: E tama Hikairo

authors: Maxwell, Te Kahautu

subjects: Oriori

abstract: He oriori tēnei mō Hikairo, te mokopuna tuatahi a Kīngi Tūheitia. He oriori tēnei e whakanui ana i a Hikairo, tōna whakapapa, tōna tūranga i te ao Māori me te ao Kīngitanga. He mokopuna Ringatū anō a Hikairo, nā Kīngi Tūheitia i tuku mai a Hikairo kia tūātia e Te Hāhi Ringatū ki te Poukai o Wāhi Pā i te tuawaru o Whiringa-ā-Nuku 2014. Ka whakaaturia tōna whakapono Hāhi Ringatū ki roto i te oriori nei e kupu whakaaritia ana. I tohua hoki e Kīngi Tūheitia a Te Kāhautu hai pou whakaruruhau1 mō Hikairo koinei ia i titoa ai tēnei oriori mō tana tamaiti mokopuna, mō Hikairo. He aroha nui nō te matua mō wai oti, mō Hikairo.

I titoa tēnei oriori hai waiatatanga mā te kapa haka o Ōpōtiki Mai Tawhiti. I waiatatia e Ōpōtiki Mai Tawhiti tēnei ki Te Matatini i tū ki Ōtautahi te tau rua mano tekau mā rima. He huarahi anō tēnei mā Te Kāhautu ki te whakamānawa i tana mokopuna i a Hikairo, nara nā te kapa haka a Te Kāhautu i waiata, i whakanui a Hikairo ki te maraenui o te iwi Māori, ko Te Matatini. Ana i tuatahi a Hikairo i te wehenga o Te Waiata Tira. “E Tama Hikairo, haere mai rā.”

text: E tama Hikairo He oriori tēnei mō Hikairo, te mokopuna tuatahi a Kīngi Tūheitia. He oriori tēnei e whakanui ana i a Hikairo, tōna whakapapa, tōna tūranga i te ao Māori me te ao Kīngitanga. He mokopuna Ringatū anō a Hikairo, nā Kīngi Tūheitia i tuku mai a Hikairo kia tūātia e Te Hāhi Ringatū ki te Poukai o Wāhi Pā i te tuawaru o Whiringa-ā-Nuku 2014. Ka whakaaturia tōna whakapono Hāhi Ringatū ki roto i te oriori nei e kupu whakaaritia ana. I tohua hoki e Kīngi Tūheitia a Te Kāhautu hai pou whakaruruhau1 mō Hikairo koinei ia i titoa ai tēnei oriori mō tana tamaiti mokopuna, mō Hikairo. He aroha nui nō te matua mō wai oti, mō Hikairo.

I titoa tēnei oriori hai waiatatanga mā te kapa haka o Ōpōtiki Mai Tawhiti. I waiatatia e Ōpōtiki Mai Tawhiti tēnei ki Te Matatini i tū ki Ōtautahi te tau rua mano tekau mā rima. He huarahi anō tēnei mā Te Kāhautu ki te whakamānawa i tana mokopuna i a Hikairo, nara nā te kapa haka a Te Kāhautu i waiata, i whakanui a Hikairo ki te maraenui o te iwi Māori, ko Te Matatini. Ana i tuatahi a Hikairo i te wehenga o Te Waiata Tira. “E Tama Hikairo, haere mai rā.”

year: 2016