A Method for Learning from Hints

We address the problem of learning an unknown function by putting together several pieces of information (hints) that we know about the function. We introduce a method that generalizes learning from examples to learning from hints. A canonical representation of hints is defined and illustrated for new types of hints. All the hints are represented to the learning process by examples, and examples of the function are treated on equal footing with the rest of the hints. During learning, examples from different hints are selected for processing according to a given schedule. We present two types of schedules; fixed schedules that specify the relative emphasis of each hint, and adaptive schedules that are based on how well each hint has been learned so far. Our learning method is compatible with any descent technique that we may choose to use

Modified Simulation Learning Method on Knowledge and Attitude of Nursing Student's Cultural Awareness at Universitas Indonesia

Nursing students should be prepared to be culturally competent nurses. Cultural awareness is believed as the most important elements of cultural competence. The purpose of this article is to describe the effectiveness of Modified Simulation Learning Methods on cultural awareness as one atribute of cultural competence. A  quasi-experimental (control group) design was used to explore the relationship between variabels among 98 first year nursing student attending Basic Nursing Concept I course at Faculty of Nursing Universitas Indonesia. The knowledge of cultural awareness was found statistically different between participants in Modified Simulation Methods group (intervention) and participants using the regular method. However, there were no statistical differences in attitude of cultural awareness between intervention and control groups. It could be concluded that Modified Simulation Learning methods is an effective learning method for increasing cultural knowledge of nusing student to be a competent nurse. Further research should be developed in continuing the improvement of cultural competence such as cultural skills

Implementasi Green Learning Method (GeLem) dalam Pengembangan Bahan Ajar Berbasis Potensi Lokal di Wana Wisata Grape, Kecamatan Wungu, Kabupaten Madiun

Pembelajaran sains sesuai hakikatnya harus meliputi proses, produk, dan sikap ilmiah. Pembelajaran mata kuliah Pendidikan Biologi di FPMIPA IKIP PGRI MADIUN memerlukan sumber/media, metode belajar yang relevan sesuai karakteristik bidang ilmu biologi. Pembuatan bahan ajar kontekstual menitikberatkan pada pengalaman mahasiswa dengan cara mengeksplorasi lingkungan riil. Wana wisata Grape memiliki tingkat biodiversitas tinggi sehingga relevan jika digunakan sebagai sumber belajar dan bahan pembuatan bahan ajar perkuliahan berbasis potensi lokal. Penerapan green learning method merupakan sarana dari upaya untuk mengeksplorasi potensi SDA di wana wisata Grape melalui pengalaman langsung dan menumbuhkan kesadaran serta peduli terhadap lingkungan. Penerapan Green Learning Method (GeLeM) dapat dilakukan di wana wisata Grape dengan menggunakan potensi alam yang ada. Penerapan tersebut dilakukan dengan cara eksplorasi potensi alam yang relevan sebagai bahan ajar, reduksi, pembahasan dan penyusunan bahan ajar bidang botani dan mikrobiologi berbasis potensi alam. Wana wisata Grape Madiun dapat dimanfaatkan sebagai sumber belajar mahasiswa dengan menggunakan Green Learning Method (GeLeM) dengan menggunakan potensi lokalnya yang berbasis natural resourches. Hasil eksplorasi menunjukkan terdapat 24 tanaman tingkat tinggi sebagai bahan ajar botani dan 3 isolat kapang uji tanah di area Wana Wisata Grape

ADADELTA: An Adaptive Learning Rate Method

We present a novel per-dimension learning rate method for gradient descent called ADADELTA. The method dynamically adapts over time using only first order information and has minimal computational overhead beyond vanilla stochastic gradient descent. The method requires no manual tuning of a learning rate and appears robust to noisy gradient information, different model architecture choices, various data modalities and selection of hyperparameters. We show promising results compared to other methods on the MNIST digit classification task using a single machine and on a large scale voice dataset in a distributed cluster environment.Comment: 6 page

Deep Transfer Learning: A new deep learning glitch classification method for advanced LIGO

The exquisite sensitivity of the advanced LIGO detectors has enabled the detection of multiple gravitational wave signals. The sophisticated design of these detectors mitigates the effect of most types of noise. However, advanced LIGO data streams are contaminated by numerous artifacts known as glitches: non-Gaussian noise transients with complex morphologies. Given their high rate of occurrence, glitches can lead to false coincident detections, obscure and even mimic gravitational wave signals. Therefore, successfully characterizing and removing glitches from advanced LIGO data is of utmost importance. Here, we present the first application of Deep Transfer Learning for glitch classification, showing that knowledge from deep learning algorithms trained for real-world object recognition can be transferred for classifying glitches in time-series based on their spectrogram images. Using the Gravity Spy dataset, containing hand-labeled, multi-duration spectrograms obtained from real LIGO data, we demonstrate that this method enables optimal use of very deep convolutional neural networks for classification given small training datasets, significantly reduces the time for training the networks, and achieves state-of-the-art accuracy above 98.8%, with perfect precision-recall on 8 out of 22 classes. Furthermore, new types of glitches can be classified accurately given few labeled examples with this technique. Once trained via transfer learning, we show that the convolutional neural networks can be truncated and used as excellent feature extractors for unsupervised clustering methods to identify new classes based on their morphology, without any labeled examples. Therefore, this provides a new framework for dynamic glitch classification for gravitational wave detectors, which are expected to encounter new types of noise as they undergo gradual improvements to attain design sensitivity

UNIVERSITY STUDENTS’ PERCEPTIONS TOWARD “PAIRED AND PROBLEMS LEARNING METHOD” IN WRITING CLASS.

Language is a communicative system as a medium for expressing thoughts and emotions, without language humans cannot connect with each other. Student perceptions refer to the way students understand and interpret information, experiences or situations encountered in the educational environment. This research used qualitative descriptive method to observe English department students’ perceptions and problems that arise in implementing paired learning methods in writing class. The respondents of this research consist of 20 English department students who have taken a paragraph writing class in the 5th semester of 2022 with minimum grade of “B” at University Muhammadiyah of Malang. The researcher distributed 3 questions related to students’ perceptions of paired learning method and the problem that arise in process of implementing paired learning method as well as criticism of paired learning method. Data collection was carries out through questionnaires and interview. The aim of this research is to analyse students' perceptions of the learning that is broadcast and the problems that arise in implementing the paired learning method in writing classes. The result of this research highlights positive perceptions and problem that arise regarding the method of implementing paired learning