Robust Loss Functions under Label Noise for Deep Neural Networks

In many applications of classifier learning, training data suffers from label noise. Deep networks are learned using huge training data where the problem of noisy labels is particularly relevant. The current techniques proposed for learning deep networks under label noise focus on modifying the network architecture and on algorithms for estimating true labels from noisy labels. An alternate approach would be to look for loss functions that are inherently noise-tolerant. For binary classification there exist theoretical results on loss functions that are robust to label noise. In this paper, we provide some sufficient conditions on a loss function so that risk minimization under that loss function would be inherently tolerant to label noise for multiclass classification problems. These results generalize the existing results on noise-tolerant loss functions for binary classification. We study some of the widely used loss functions in deep networks and show that the loss function based on mean absolute value of error is inherently robust to label noise. Thus standard back propagation is enough to learn the true classifier even under label noise. Through experiments, we illustrate the robustness of risk minimization with such loss functions for learning neural networks.Comment: Appeared in AAAI 201

Signal Recovery in Perturbed Fourier Compressed Sensing

In many applications in compressed sensing, the measurement matrix is a Fourier matrix, i.e., it measures the Fourier transform of the underlying signal at some specified `base' frequencies $\{u_i\}_{i=1}^M$, where $M$ is the number of measurements. However due to system calibration errors, the system may measure the Fourier transform at frequencies $\{u_i + \delta_i\}_{i=1}^M$ that are different from the base frequencies and where $\{\delta_i\}_{i=1}^M$ are unknown. Ignoring perturbations of this nature can lead to major errors in signal recovery. In this paper, we present a simple but effective alternating minimization algorithm to recover the perturbations in the frequencies \emph{in situ} with the signal, which we assume is sparse or compressible in some known basis. In many cases, the perturbations $\{\delta_i\}_{i=1}^M$ can be expressed in terms of a small number of unique parameters $P \ll M$. We demonstrate that in such cases, the method leads to excellent quality results that are several times better than baseline algorithms (which are based on existing off-grid methods in the recent literature on direction of arrival (DOA) estimation, modified to suit the computational problem in this paper). Our results are also robust to noise in the measurement values. We also provide theoretical results for (1) the convergence of our algorithm, and (2) the uniqueness of its solution under some restrictions.Comment: New theortical results about uniqueness and convergence now included. More challenging experiments now include

The Lack of Protection Afforded Software under the Current Intellectual Property Laws

Many abstract advances in computer technology remain unprotected since the current intellectual property system has been shaped through a focus on tangible, physical inventions. The software industry in the United States accounts for domestic revenues of over fifty billion dollars each year in worldwide sales and services. Accordingly, it is imperative that United States software developers be provided adequate intellectual property coverage in order to protect existing technology and encourage further innovation in the field. The present lack of adequate protection has handicapped American developers unnecessarily in the global software market

Advances in DNA Affinity Chromatography

Different aspects of DNA affinity chromatography such as DNA complexity heparin elution, the Bi-column method and the oligonucluotide trapping method were studied. The complexity (length) of a DNA sequence attached to an affinity chromatography column affects column retention, and the purity of transcription factors obtained. T18: A18 tailed DNA affinity columns were better suited for purification of most of the transcription factors than either the discrete or concatemeric DNA affinity columns. A novel method using heparin for eluting transcription factors from DNA Sepharose columns was characterized. The amount of the lac repressor chimera which eluted from the column was shown to increase with increases in the mobile phase heparin concentration. The elution of the protein was also shown to be dependent on the amount of DNA coupled to the column and more protein eluted from columns containing lesser amounts of DNA. These data suggest that heparin and DNA compete for binding to the protein; this competition causes elution. Comparison of heparin- and salt-eluted protein demonstrated the heparin-eluted fraction of lac repressor was significantly purer than that eluted with salt and comparable to that obtained by elution with the specific ligand IPTG, a lactose analog. A novel Bi-column method was developed in which lac repressor is eluted from the Op1-Sepharose with a low heparin concentration and trapped on a Op1T18-Sepharose column because of its higher affinity for the lac repressor protein. Elution of the latter column with buffer containing a high salt concentration gives significantly purer transcription factor than the conventionally used single column methods and removes residual heparin. Highly pure CAAT enhancer binding protein(C/EBP) and the B3 transcription factor are also obtained by using variants of this Bi-column method. A new oligonucleotide trapping method in which a short oligonucleotide coupled to Sepharose is used to trap a complex of the transcription factor and its corresponding specific DNA sequence was developed. Highly purified transcription factor B3 was obtained using the oligonucleotide trapping method

Adiabatic Logic-in-Memory Architecture

An adiabatic logic-in-memory based complementary metal- oxide-semiconductor/magnetic-tunnel-junction (ALiM CMOS/MTJ) circuit utilizes an adiabatic logic based pre- charged sense amplifier (PCSA) to recover energy from its output load capacitors. The ALiM CMOS/MTJ includes a non-volatile magnetic-tunnel-junction (MTJ) based memory. The ALiM CMOS/MTJ also includes a dual rail complementary metal-oxide-semiconductor (CMOS) logic that performs logic operations in association with the MTJ, and thereby generates logic outputs based on logic inputs. The ALiM CMOS/MTJ also includes the adiabatic PCSA, which is operatively coupled to the dual rail CMOS logic. The adiabatic logic based PCSA includes PCSA circuitry for which an input is a multi-phase power clock, and a charge recovery circuit having the output load capacitors. The charge recovery circuit is operatively coupled to the PCSA circuitry such that the ALiM CMOS/MTJ circuit uses the power clock to recover energy from the output load capacitors

GIS BASED MORPHOMETRIC CHARACTERISTICS OF KADAVANAR RIVER BASIN IN TAMIL NADU, INDIA

The Remote Sensing and GIS technique is an effective tool for analyzing the morphological characteristics of a river basin. The geographical location of Kadavanar river basin between latitudes 10° 52' 34.70"N and 10° 10' 57.59"N, and longitudes 77° 37' 48.14"E and 78° 13' 27.69"E, and one of the contributors to Cauvery river. The study focused on the river basin linear, areal, and relief aspects of morphometric characteristics. The study concentrated on the morphometric parameters and evolution of the stream order (U), stream length (Lu), bifurcation ratio (Rb), drainage density (Dd), stream frequency (Fs), drainage texture (Rt), elongation ratio (Re), circularity ratio (Rc), form factor (Rf), basin relief (Bh), relief ratio (Rh) and ruggedness number (Rn). The Kadavanar basin has a six-order of the drainage system, with a total of 841 stream networks, of which are 653 in the first-order, 143 in the second-order, 34 in the third-order, 8 in the fourth-order, 2 in the fifth-order stream, and 1 in the sixth-order stream according to morphometric study. The first order of the stream has a longer overall length, which decreases as the stream order increases. The average bifurcation ratio is 3.80, signifying that there were more structural disruptions due to geological influence. There has observed a low drainage density of the value of 0.91 km/km2. It indicates that the river basin has a dense vegetation cover and is highly permeable. The basin morphometric study revealed that it has a slight risk of soil erosion and flood of the basin, indicating that surface runoff of the upland region of the river basin is significantly infiltration gently downstream of the basin, contributing to the groundwater potentiality of the region. Further study of Remote Sensing and GIS techniques is more effective in developing an appropriate natural resource for the groundwater management system of the region